Final Year IEEE Project 2013-2014 - Bio Medical Engineering Project Title and Abstract

Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad |

Pondicherry | Trivandrum | Salem | Erode | Tirunelveli

http://www.elysiumtechnologies.com, [email protected]

13 Years of Experience

Automated Services

24/7 Help Desk Support

Experience & Expertise Developers

Advanced Technologies & Tools

Legitimate Member of all Journals

Having 1,50,000 Successive records in

all Languages

More than 12 Branches in Tamilnadu,

Kerala & Karnataka.

Ticketing & Appointment Systems.

Individual Care for every Student.

Around 250 Developers & 20

Researchers




227-230 Church Road, Anna Nagar, Madurai – 625020.

0452-4390702, 4392702, + 91-9944793398.

[email protected], [email protected]

S.P.Towers, No.81 Valluvar Kottam High Road, Nungambakkam,

Chennai - 600034. 044-42072702, +91-9600354638,

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627007. 0462-2532104, +919677733255,

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Road, Opp. Bus stand, Erode-638 011. 0424-4030055, +91-

9677748477 [email protected]

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4200640 +91-9677704822

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TNHB A-Block, D.no.10, Opp: Hotel Ganesh Near Busstand. Salem

– 636007, 0427-4042220, +91-9894444716.

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ETPL

BME-001

Convolving Engineering and Medical Pedagogies for Training of Tomorrow's Health

Care Professionals

Abstract: Several fundamental benefits justify why biomedical engineering and medicine should form a

more convergent alliance, especially for the training of tomorrow's physicians and biomedical engineers.

Herein, we review the rationale underlying the benefits. Biological discovery has advanced beyond the

era of molecular biology well into today's era of molecular systems biology, which focuses on

understanding the rules that govern the behavior of complex living systems. This has important medical

implications. To realize cost-effective personalized medicine, it is necessary to translate the advances in

molecular systems biology to higher levels of biological organization (organ, system, and organismal

levels) and then to develop new medical therapeutics based on simulation and medical informatics

analysis. Higher education in biological and medical sciences must adapt to a new set of training

objectives. This will involve a shifting away from reductionist problem solving toward more integrative,

continuum, and predictive modeling approaches which traditionally have been more associated with

engineering science. Future biomedical engineers and MDs must be able to predict clinical response to

therapeutic intervention. Medical education will involve engineering pedagogies, wherein basic governing

rules of complex system behavior and skill sets in manipulating these systems to achieve a practical

desired outcome are taught. Similarly, graduate biomedical engineering programs will include more

practical exposure to clinical problem solving.

ETPL

BME-002

Accurate Dialysis Dose Evaluation and Extrapolation Algorithms During Online

Optical Dialysis Monitoring

Abstract: The aim of this study was to propose an improved method for accurate dialysis dose evaluation

and extrapolation by means of Kt/$V$ from online UV-absorbance measurements for real time and

continuous treatment monitoring. The study included a total of 24 treatments from ten uremic patients,

seven of whom were male and three females. All patients were on chronic thrice-weekly hemodialysis

therapy. The study included both stable and unstable treatments. A known signal processing algorithm,

Levenberg–Marquardt, and the newly developed SMART were utilized for the removal of disturbances

not relevant for dialysis dose evaluation. Finally, the results were compared with the Kt/$V$ values based

on the blood samples. The new data processing algorithm, SMART, removes disturbances, helps estimate

the online Kt/$V$ with significant precision increase and without any time delay, and more effectively

predicts the end Kt/$V$ for the treatment than the known algorithms.

ETPL

BME-003 Toward Robot-Assisted Neurosurgical Lasers

Abstract: Despite the potential increase in precision and accuracy, laser technology is not widely used in

neurological surgery. This in part relates to challenges associated with the early introduction of lasers into

neurosurgery. Considerable advances in laser technology have occurred, which together with robotic

technology could create an ideal platform for neurosurgical application. In this study, a 980-nm contact

diode laser was integrated with neuroArm. Preclinical evaluation involved partial hepatectomy, bilateral



http://www.elysiumtechnologies.com, [email protected] nephrectomy, splenectomy, and bilateral submandibular gland excision in a Sprague-Dawley rat model (n

= 50). Total surgical time, blood loss as weight of surgical gauze before and after the procedure, and the

incidence of thermal, vascular, or lethal injury were recorded and converted to an overall performance

score. Thermal damage was evaluated in the liver using tissue samples stained with hematoxylin and

eosin. Clinical studies involved step-wise integration of the 980-nm laser system into four neurosurgical

cases. Results demonstrate the successful integration of contact laser technology into microsurgery, with

and without robotic assistance. In preclinical studies, the laser improved microsurgical performance and

reduced thermal damage, while neuroArm decreased intra- and intersurgeon variability. Clinical studies

demonstrate dutility in meningioma resection (n = 4). Together, laser and robotic technology offered a

more consistent, expedient, and precise tool for microsurgery.

ETPL

BME-004

Relevance of Laser Doppler and Laser Speckle Techniques for Assessing Vascular

Function: State of the Art and Future Trend

Abstract: In clinical and research applications, the assessment of vascular function has become of major

importance to evaluate and follow the evolution of cardiovascular pathologies, diabetes, hypertension, or

foot ulcers. Therefore, the development of engineering methodologies able to monitor noninvasively

blood vessel activities-such as endothelial function-is a significant and emerging challenge. Laser-based

techniques have been used to respond-as much as possible-to these requirements. Among them, laser

Doppler flowmetry (LDF) and laser Doppler imaging (LDI) were proposed a few decades ago. They

provide interesting vascular information but possess drawbacks that prevent an easy use in some clinical

situations. Recently, the laser speckle contrast imaging (LSCI) technique, a noninvasive camera-based

tool, was commercialized and overcomes some of the LDF and LDI weaknesses. Our paper describes

how-using engineering methodologies-LDF, LDI, and LSCI can meet the challenging clinician needs in

assessing vascular function, with a special focus on the state of the art and future trends.

ETPL

BME-005 Quantitative Analysis of Locomotive Behavior of Human Sperm Head and Tail

Abstract: Sperm selection plays a significant role in in vitro fertilization (IVF). Approaches for assessing

sperm quality include noninvasive techniques based on sperm morphology and motility as well as

invasive techniques for checking DNA integrity. In 2006, a new device using hyaluronic acid (HA)-

coated dish for sperm selection was cleared by the Food and Drug Administration (FDA) and entered IVF

clinics. In this technique, only sperms with DNA integrity bind to the HA droplet, after which these

bound sperm stop revealing head motion and their tail movement becomes more vigorous. However,

selecting a single sperm cell from among HA-bound sperms is ad hoc in IVF clinics. Different from

existing sperm tracking algorithms that are largely limited to tracking sperm head only and are only able

to track one sperm at a time, this paper presents a multisperm tracking algorithm that tracks both sperm

heads and low-contrast sperm tails. The tracking results confirm a significant correlation between sperm

head velocity and tail beating amplitude, demonstrate that sperms bound to HA generally have a higher

velocity (before binding) than those sperms that are not able to bind to HA microdots, and quantitatively

reveal that HA-bound sperms' tail beating amplitudes are different among HA-bound sperms.




ETPL

BME-006

Grand Challenge: Applying Regulatory Science and Big Data to Improve Medical

Device Innovation

Abstract: Understanding how proposed medical devices will interface with humans is a major challenge

that impacts both the design of innovative new devices and approval and regulation of existing devices.

Today, designing and manufacturing medical devices requires extensive and expensive product cycles.

Bench tests and other preliminary analyses are used to understand the range of anatomical conditions, and

animal and clinical trials are used to understand the impact of design decisions upon actual device

success. Unfortunately, some scenarios are impossible to replicate on the bench, and competitive

pressures often accelerate initiation of animal trials without sufficient understanding of parameter

selections. We believe that these limitations can be overcome through advancements in data-driven and

simulation-based medical device design and manufacturing, a research topic that draws upon and

combines emerging work in the areas of Regulatory Science and Big Data. We propose a cross-

disciplinary grand challenge to develop and holistically apply new thinking and techniques in these areas

to medical devices in order to improve and accelerate medical device innovation.

ETPL

BME-007 Coaxial Needle Insertion Assistant With Enhanced Force Feedback

Abstract: Many medical procedures involving needle insertion into soft tissues, such as anesthesia,

biopsy, brachytherapy, and placement of electrodes, are performed without image guidance. In such

procedures, haptic detection of changing tissue properties at different depths during needle insertion is

important for needle localization and detection of subsurface structures. However, changes in tissue

mechanical properties deep inside the tissue are difficult for human operators to sense, because the

relatively large friction force between the needle shaft and the surrounding tissue masks the smaller tip

forces. A novel robotic coaxial needle insertion assistant, which enhances operator force perception, is

presented. This one-degree-of-freedom cable-driven robot provides to the operator a scaled version of the

force applied by the needle tip to the tissue, using a novel design and sensors that separate the needle tip

force from the shaft friction force. The ability of human operators to use the robot to detect membranes

embedded in artificial soft tissue was tested under the conditions of 1) tip force and shaft force feedback,

and 2) tip force only feedback. The ratio of successful to unsuccessful membrane detections was

significantly higher (up to 50%) when only the needle tip force was provided to the user.

ETPL

BME-008

Reducing False Intracranial Pressure Alarms Using Morphological Waveform

Features

Abstract: False alarms produced by patient monitoring systems in intensive care units are a major issue

that causes alarm fatigue, waste of human resources, and increased patient risks. While alarms are

typically triggered by manually adjusted thresholds, the trend and patterns observed prior to threshold

crossing are generally not used by current systems. This study introduces and evaluates, a smart alarm

detection system for intracranial pressure signal (ICP) that is based on advanced pattern recognition

methods. Models are trained in a supervised fashion from a comprehensive dataset of 4791 manually



http://www.elysiumtechnologies.com, [email protected] labeled alarm episodes extracted from 108 neurosurgical patients. The comparative analysis provided

between spectral regression, kernel spectral regression, and support vector machines indicates the

significant improvement of the proposed framework in detecting false ICP alarms in comparison to a

threshold-based technique that is conventionally used. Another contribution of this work is to exploit an

adaptive discretization to reduce the dimensionality of the input features. The resulting features lead to a

decrease of 30% of false ICP alarms without compromising sensitivity.

ETPL

BME-009 Grand Challenges in Bioengineered Nanorobotics for Cancer Therapy

Abstract: One of the grand challenges currently facing engineering, life sciences, and medicine is the

development of fully functional nanorobots capable of sensing, decision making, and actuation. These

nanorobots may aid in cancer therapy, site-specific drug delivery, circulating diagnostics, advanced

surgery, and tissue repair. In this paper, we will discuss, from a bioinspired perspective, the challenges

currently facing nanorobotics, including core design, propulsion and power generation, sensing, actuation,

control, decision making, and system integration. Using strategies inspired from microorganisms, we will

discuss a potential bioengineered nanorobot for cancer therapy.

ETPL

BME-010 Neuromodulation for Brain Disorders: Challenges and Opportunities

Abstract: The field of neuromodulation encompasses a wide spectrum of interventional technologies that

modify pathological activity within the nervous system to achieve a therapeutic effect. Therapies

including deep brain stimulation, intracranial cortical stimulation, transcranial direct current stimulation,

and transcranial magnetic stimulation have all shown promising results across a range of neurological and

neuropsychiatric disorders. While the mechanisms of therapeutic action are invariably different among

these approaches, there are several fundamental neuroengineering challenges that are commonly

applicable to improving neuromodulation efficacy. This paper reviews the state-of-the-art of

neuromodulation for brain disorders and discusses the challenges and opportunities available for

clinicians and researchers interested in advancing neuromodulation therapies.

ETPL

BME-011 Minimizing Cytosol Dilution in Whole-Cell Patch-Clamp Experiments

Abstract: During a conventional whole-cell patch clamp experiment, diffusible cytosolic ions or

molecules absent in the pipette solution can become diluted by a factor of one million or more, leading to

diminished current or fluorescent signals. Existing methods to prevent or limit cytosol diffusion include

reducing the diameter of the pipette's orifice, adding cytosolic extract or physiological entities to the

pipette solution, and using the perforated patch clamp configuration. The first method introduces

measurement error in recorded signals from increased series resistance and the latter two are cumbersome

to perform. In addition, most perforated patch configurations, prevent investigators from using test

compounds in the pipette solution. We present a method to overcome these limitations by minimizing



http://www.elysiumtechnologies.com, [email protected] cytosol dilution using a novel pipette holder. Cell-attached configuration is obtained with the pipette filled

with pipette solution. Most of the pipette solution is then replaced with mineral oil so that cytosol dilution

can be minimized in whole-cell configuration. To accomplish this requires a suction line and two

Ag/AgCl electrodes inside the pipette. Testing our novel pipette holder with Chinese Hamster Ovarian

cells, we demonstrate cytosol dilution factors between 76 and 234. For large cells with somas greater than

40 μm, cytosol dilution factors of 10 or less are achievable.

ETPL

BME-012 Engineering Stem Cells For Future Medicine

Abstract: Despite their great potential in regenerative medicine applications, stem cells (especially

pluripotent ones) currently show a limited clinical success, partly due to a lack of biological knowledge,

but also due to a lack of specific and advanced technological instruments able to overcome the current

boundaries of stem cell functional maturation and safe/effective therapeutic delivery. This paper aims at

describing recent insights, current limitations, and future horizons related to therapeutic stem cells, by

analyzing the potential of different bioengineering disciplines in bringing stem cells toward a safe clinical

use. First, we clarify how and why stem cells should be properly engineered and which could be in a near

future the challenges and the benefits connected with this process. Second, we identify different routes

toward stem cell differentiation and functional maturation, relying on chemical, mechanical,

topographical, and direct/indirect physical stimulation. Third, we highlight how multiscale modeling

could strongly support and optimize stem cell engineering. Finally, we focus on future robotic tools that

could provide an added value to the extent of translating basic biological knowledge into clinical

applications, by developing ad hoc enabling technologies for stem cell delivery and control.

ETPL

BME-013

Surgical Robotics Through a Keyhole: From Today's Translational Barriers to

Tomorrow's ―Disappearing‖ Robots,

Abstract: In the last century, engineering advances have transformed the practice of surgery. Keyhole

surgical techniques offer a number of advantages over traditional open approaches including less

postoperative pain, fewer wound complications, and reduced length of stay in hospital. However, they

also present considerable technical challenges, particularly to surgeons performing new operative

approaches, such as those through natural orifices. Advances in surgical robots have improved surgical

visualization, dexterity, and manipulation consistency, thus greatly enhancing surgical performance and

patient care. Clinically, however, robotic surgery is still in its infancy, and its use has remained limited to

relatively few operations. In the paper, we will discuss the economic-, clinical-, and research-related

factors that may act as barriers to the widespread utilization and development of surgical robots. In

overcoming these barriers through a synergistic effort of both engineering and medicine, we highlight our

future vision of robotic surgery, in both the short and long term.

ETPL

BME-014

Continuous Detection of Muscle Aspect Ratio Using Keypoint Tracking in

Ultrasonography




Abstract: Muscle aspect ratio of cross-sectional area is one of the most widely used parameters for

quantifying muscle function in both diagnosis and rehabilitation assessment. Ultrasound imaging has been

frequently used to noninvasively study the characteristics of human muscles as a reliable method.

However, the aspect ratio measurement is traditionally conducted by the manual digitization of reference

points; thus, it is subjective, time-consuming, and prone to errors. In this paper, a novel method is

proposed to continuously detect the muscle aspect ratio. Two keypoint pairs are manually digitized on the

lateral and longitudinal borders at the first frame, and automatically tracked by an optical flow technique

at the subsequent frames. The muscle aspect ratio is thereby obtained based on the estimated muscle

width and thickness. Six ultrasound sequences from different subjects are used to evaluate this method,

and the overall coefficient of multiple correlation of the results between manual and proposed methods is

0.97 ± 0.02. The linear regression shows that a good linear correlation

ETPL

BME-015

Multi-Field-of-View Framework for Distinguishing Tumor Grade in ER+ Breast

Cancer From Entire Histopathology Slides

Abstract: Modified Bloom–Richardson (mBR) grading is known to have prognostic value in breast cancer

(BCa), yet its use in clinical practice has been limited by intra- and interobserver variability. The

development of a computerized system to distinguish mBR grade from entire estrogen receptor-positive

(ER+) BCa histopathology slides will help clinicians identify grading discrepancies and improve overall

confidence in the diagnostic result. In this paper, we isolate salient image features characterizing tumor

morphology and texture to differentiate entire hematoxylin and eosin (H and E) stained histopathology

slides based on mBR grade. The features are used in conjunction with a novel multi-field-of-view (multi-

FOV) classifier—a whole-slide classifier that extracts features from a multitude of FOVs of varying

sizes—to identify important image features at different FOV sizes. Image features utilized include those

related to the spatial arrangement of cancer nuclei (i.e., nuclear architecture) and the textural patterns

within nuclei (i.e., nuclear texture). Using slides from 126 ER+ patients (46 low, 60 intermediate, and 20

high mBR grade), our grading system was able to distinguish low versus high, low versus intermediate,

and intermediate versus high grade patients with area under curve values of 0.93, 0.72, and 0.74,

respectively. Our results suggest that the multi-FOV classifier is able to 1) successfully discriminate low,

medium, and high mBR grade and 2) identify specific image features at different FOV sizes that are

important for distinguishing mBR grade in H and E stained ER+ BCa histology slides.

ETPL

BME-016 Simplified Design Equations for Class-E Neural Prosthesis Transmitters

Abstract: Extreme miniaturization of implantable electronic devices is recognized as essential for the next

generation of neural prostheses, owing to the need for minimizing the damage and disruption of the

surrounding neural tissue. Transcutaneous power and data transmission via a magnetic link remains the

most effective means of powering and controlling implanted neural prostheses. Reduction in the size of

the coil, within the neural prosthesis, demands the generation of a high-intensity radio frequency magnetic

field from the extracoporeal transmitter. The Class-E power amplifier circuit topology has been



http://www.elysiumtechnologies.com, [email protected] recognized as a highly effective means of producing large radio frequency currents within the transmitter

coil. Unfortunately, design of a Class-E circuit is most often fraught by the need to solve a complex set of

equations so as to implement both the zero-voltage-switching and zero-voltage-derivative-switching

conditions that are required for efficient operation. This paper presents simple explicit design equations

for designing the Class-E circuit topology. Numerical design examples are presented to illustrate the

design procedure.

ETPL

BME-017

A 3-D Reconstruction Solution to Current Density Imaging Based on Acoustoelectric

Effect by Deconvolution: A Simulation Study

Abstract: Hybrid imaging modality combining ultrasound scanning and electrical current density imaging

through the acoustoelectric (AE) effect may potentially provide solutions to imaging electrical activities

and properties of biological tissues with high spatial resolution. In this study, a 3-D reconstruction

solution to ultrasound current source density imaging (UCSDI) by means of Wiener deconvolution is

proposed and evaluated through computer simulations. As compared to previous 2-D UCSDI problem, in

a 3-D volume conductor with broadly distributed current density field, the AE signal becomes a 3-D

convolution between the electric field and the acoustic field, and effective 3-D reconstruction algorithm

has not been developed so far. In the proposed method, a 3-D ultrasound scanning is performed while the

corresponding AE signals are collected from multiple electrode pairs attached on the surface of the

imaging object. From the collected AE signals, the acoustic field and electric field were first decoupled by

Wiener deconvolution. Then, the current density distribution was reconstructed by inverse projection. Our

simulations using artificial current fields in homogeneous phantoms suggest that the proposed method is

feasible and robust against noise. It is also shown that using the proposed method, it is feasible to

reconstruct 3-D current density distribution in an inhomogeneous conductive medium.

ETPL

BME-018

Applying Combined Optical Tweezers and Fluorescence Microscopy Technologies to

Manipulate Cell Adhesions for Cell-to-Cell Interaction Study

Abstract: Cell-to-cell interactions are important for the regulation of various cell activities, such as

proliferation, differentiation, and apoptosis. This paper presents an approach to studying cell-to-cell

interactions at a single-cell level through manipulating cell adhesions with optical tweezers. Experiments

are performed on leukemia cancer cells and stromal cells to demonstrate the feasibility of this method.

After the adhesion properties of leukemia cells on stromal cells are characterized, fluorescence intensity is

used as a label to study the Wnt signaling pathway of leukemia cells. The activities of the Wnt signaling

pathway of K562 cells on M210B4 and HS5 cells are examined based on fluorescence analysis. The

reliability of the fluorescence imaging is confirmed through comparison with traditional flow cytometry

analysis. The proposed approach will offer new avenues to investigate otherwise inaccessible mechanisms

in cell-to-cell interactions.

ETPL

BME-019 Far-Field RF Powering of Implantable Devices: Safety Considerations




Abstract: Far-field RF powering is an attractive solution to the challenge of remotely powering devices

implanted in living tissue. The purpose of this study is to characterize the peak obtainable power levels in

a wireless myoelectric sensor implanted in a patient while maintaining safe local temperature and RF

powering conditions. This can serve as a guide for the design of onboard electronics in related medical

implants and provide motivation for more efficient power management strategies for implantable

integrated circuits. Safe powering conditions and peak received power levels are established using a

simplified theoretical analysis and Federal Communications Commission-established limits for radiating

antennas. These conditions are subsequently affirmed and improved upon using the finite-element method

and temperature modeling in bovine muscle.

ETPL

BME-020

Blood Perfusion Values of Laser Speckle Contrast Imaging and Laser Doppler

Flowmetry: Is a Direct Comparison Possible?

Abstract: Laser Doppler flowmetry (LDF) and laser speckle contrast imaging (LSCI) allow the

monitoring of microvascular blood perfusion. The relationship between the measurements obtained by

these two techniques remains unclear. In the present contribution, we demonstrate, experimentally and

theoretically, that skin blood flow measurements obtained by LDF and LSCI techniques cannot be

compared directly even after ―classical‖ normalization procedure. This technical problem is generated by

the nonlinear relationship existing between LDF and LSCI flow data. The experiments have been

performed on five healthy voluntary subjects (forearm) by using repeated ischemia/reperfusion cycles to

induce the necessary skin blood flow changes. LDF and LSCI data were simultaneously acquired on the

same region of interest. Considering the importance of this problem from the clinical point of view, it is

concluded that the definition of new corrected algorithms for LSCI is probably a mandatory step that must

be taken into account if LDF and LSCI blood flow have to be compared.

ETPL

BME-021

Assessing the Effects of Pharmacological Agents on Respiratory Dynamics Using Time-

Series Modeling

Abstract: Developing quantitative descriptions of how stimulant and depressant drugs affect the

respiratory system is an important focus in medical research. Respiratory variables-respiratory rate, tidal

volume, and end tidal carbon dioxide-have prominent temporal dynamics that make it inappropriate to use

standard hypothesis-testing methods that assume independent observations to assess the effects of these

pharmacological agents. We present a polynomial signal plus autoregressive noise model for analysis of

continuously recorded respiratory variables. We use a cyclic descent algorithm to maximize the

conditional log likelihood of the parameters and the corrected Akaike's information criterion to choose

simultaneously the orders of the polynomial and the autoregressive models. In an analysis of respiratory

rates recorded from anesthetized rats before and after administration of the respiratory stimulant

methylphenidate, we use the model to construct within-animal z-tests of the drug effect that take account

of the time-varying nature of the mean respiratory rate and the serial dependence in rate measurements.

We correct for the effect of model lack-of-fit on our inferences by also computing bootstrap confidence

intervals for the average difference in respiratory rate pre- and postmethylphenidate treatment. Our time-



http://www.elysiumtechnologies.com, [email protected] series modeling quantifies within each animal the substantial increase in mean respiratory rate and

respiratory dynamics following methylphenidate administration. This paradigm can be readily adapted to

analyze the dynamics of other respiratory variables before and after pharmacologic treatments.

ETPL

BME-022

2-D–3-D Frequency Registration Using a Low-Dose Radiographic System for Knee

Motion Estimation

Abstract: In this paper, a new method is presented to study the feasibility of the pose and the position

estimation of bone structures using a low-dose radiographic system, the entrepreneurial operating system

(designed by EOS-Imaging Company). This method is based on a 2-D-3-D registration of EOS bi-planar

X-ray images with an EOS 3-D reconstruction. This technique is relevant to such an application thanks to

the EOS ability to simultaneously make acquisitions of frontal and sagittal radiographs, and also to

produce a 3-D surface reconstruction with its attached software. In this paper, the pose and position of a

bone in radiographs is estimated through the link between 3-D and 2-D data. This relationship is

established in the frequency domain using the Fourier central slice theorem. To estimate the pose and

position of the bone, we define a distance between the 3-D data and the radiographs, and use an iterative

optimization approach to converge toward the best estimation. In this paper, we give the mathematical

details of the method. We also show the experimental protocol and the results, which validate our

approach.

ETPL

BME-023

The Transesophageal Echocardiography Simulator Based on Computed Tomography

Images

Abstract: Simulators are a new tool in education in many fields, including medicine, where they greatly

improve familiarity with medical procedures, reduce costs, and, importantly, cause no harm to patients.

This is so in the case of transesophageal echocardiography (TEE), in which the use of a simulator

facilitates spatial orientation and helps in case studies. The aim of the project described in this paper is to

simulate an examination by TEE. This research makes use of available computed tomography data to

simulate the corresponding echocardiographic view. This paper describes the essential characteristics that

distinguish these two modalities and the key principles of the wave phenomena that should be considered

in the simulation process, taking into account the conditions specific to the echocardiography. The

construction of the CT2TEE (Web-based TEE simulator) is also presented. The considerations include

ray-tracing and ray-casting techniques in the context of ultrasound beam and artifact simulation. An

important aspect of the interaction with the user is raised.

ETPL

BME-024

Quantitative Evaluation of Two-Factor Analysis Applied to Hepatic Perfusion Study

Using Contrast-enhanced Ultrasound,

Abstract: Focal liver lesions (FLLs) are usually quantitatively assessed by time-intensity curves (TICs)

extracted from contrast-enhanced ultrasound (CEUS) image sequences. To overcome the subjectivity of

manual region of interest (ROI) selection and automatically extract TICs, a novel factor analysis method

called replace approximation (RA) was proposed. Assuming that the two factors are the arterial and portal



http://www.elysiumtechnologies.com, [email protected] vein phases, respectively, the high-dimensional time-series data are mapped into 1-D space, where the

TIC at each pixel in the image becomes a point along a one-dimensional axis. The RA method aims to

seek two apexes corresponding to the factor curves (the targeted TICs) in the subspace. This method was

tested on 18 free-breathing datasets with respiratory motion correction. The experimental results showed

that the RA method extracted physiological factor curves and the corresponding factor images efficiently.

The mean correlation coefficient between the factor curves and the corresponding ROI measurements was

0.95 ± 0.02. Furthermore, the wash-in time ratio indexes of FLLs derived from the factor curves were

used to perform parametric imaging, which could represent the characteristics of different types of FLLs.

These results indicate that two-factor analysis has the potential to perform quantitative analysis of hepatic

perfusion, which would be helpful to the differential diagnosis of FLLs.

ETPL

BME-025

Evaluation of Optical Coherence Tomography for the Measurement of the Effects of

Activators and Anticoagulants on the Blood Coagulation In Vitro

Abstract: Optical properties of human blood during coagulation were studied using optical coherence

tomography (OCT) and the parameter of clotting time derived from the 1/$e$ light penetration depth

$(d_{1/e})$ versus time was developed in our previous work. In this study, in order to know if a new

OCT test can characterize the blood-coagulation process under different treatments in vitro, the effects of

two different activators (calcium ions and thrombin) and anticoagulants, i.e., acetylsalicylic acid (ASA, a

well-known drug aspirin) and melagatran (a direct thrombin inhibitor), at various concentrations are

evaluated. A swept-source OCT system with a 1300 nm center wavelength is used for detecting the

blood-coagulation process in vitro under a static condition. A dynamic study of $d_{1/e}$ reveals a

typical behavior due to coagulation induced by both calcium ions and thrombin, and the clotting time is

concentration-dependent. Dose-dependent ASA and melagatran prolong the clotting times. ASA and

melagatran have different effects on blood coagulation. As expected, melagatran is much more effective

than ASA in anticoagulation by the OCT measurements. The OCT assay appears to be a simple method

for the measurement of blood coagulation to assess the effects of activators and anticoagulants, which can

be used for activator and anticoagulant screening.

ETPL

BME-026 Classification of Simultaneous Movements Using Surface EMG Pattern Recognition

Abstract: Advanced upper limb prostheses capable of actuating multiple degrees of freedom (DOFs) are

now commercially available. Pattern recognition algorithms that use surface electromyography (EMG)

signals show great promise as multi-DOF controllers. Unfortunately, current pattern recognition systems

are limited to activate only one DOF at a time. This study introduces a novel classifier based on Bayesian

theory to provide classification of simultaneous movements. This approach and two other classification

strategies for simultaneous movements were evaluated using nonamputee and amputee subjects

classifying up to three DOFs, where any two DOFs could be classified simultaneously. Similar results

were found for nonamputee and amputee subjects. The new approach, based on a set of conditional

parallel classifiers was the most promising with errors significantly less ( $p < 0.05$) than a single linear

discriminant analysis (LDA) classifier or a parallel approach. For three-DOF classification, the



http://www.elysiumtechnologies.com, [email protected] conditional parallel approach had error rates of 6.6% on discrete and 10.9% on combined motions, while

the single LDA had error rates of 9.4% on discrete and 14.1% on combined motions. The low error rates

demonstrated suggest than pattern recognition techniques on surface EMG can be extended to identify

simultaneous movements, which could provide more life-like motions for amputees compared to

exclusively classifying sequential movements.

ETPL

BME-027

Simultaneous Design of FIR Filter Banks and Spatial Patterns for EEG Signal

Classification

Abstract: The spatial weights for electrodes called common spatial pattern (CSP) are known to be

effective in EEG signal classification for motor imagery-based brain-computer interface (MI-BCI). To

achieve accurate classification in CSP, it is necessary to find frequency bands that relate to brain activities

associated with BCI tasks. Several methods that determine such a set of frequency bands have been

proposed. However, the existing methods cannot find the multiple frequency bands by using only learning

data. To address this problem, we propose discriminative filter bank CSP (DFBCSP) that designs finite

impulse response filters and the associated spatial weights by optimizing an objective function which is a

natural extension of that of CSP. The optimization is conducted by sequentially and alternatively solving

subproblems into which the original problem is divided. By experiments, it is shown that DFBCSP can

effectively extract discriminative features for MI-BCI. Moreover, experimental results exhibit that

DFBCSP can detect and extract the bands related to brain activities of motor imagery.

ETPL

BME-028

Development of Surrogate Spinal Cords for the Evaluation of Electrode Arrays Used in

Intraspinal Implants

Abstract: We report the development of a surrogate spinal cord for evaluating the mechanical suitability

of electrode arrays for intraspinal implants. The mechanical and interfacial properties of candidate

materials (including silicone elastomers and gelatin hydrogels) for the surrogate cord were tested. The

elastic modulus was characterized using dynamic mechanical analysis, and compared with values of

actual human spinal cords from the literature. Forces required to indent the surrogate cords to specified

depths were measured to obtain values under static conditions. Importantly, to quantify surface properties

in addition to mechanical properties normally considered, interfacial frictional forces were measured by

pulling a needle out of each cord at a controlled rate. The measured forces were then compared to those

obtained from rat spinal cords. Formaldehyde-crosslinked gelatin, 12 wt% in water, was identified as the

most suitable material for the construction of surrogate spinal cords. To demonstrate the utility of

surrogate spinal cords in evaluating the behavior of various electrode arrays, cords were implanted with

two types of intraspinal electrode arrays (one made of individual microwires and another of microwires

anchored with a solid base), and cord deformation under elongation was evaluated. The results

demonstrate that the surrogate model simulates the mechanical and interfacial properties of the spinal

cord, and enables in vitro screening of intraspinal implants.

ETPL

BME-029

Compressed Sensing for Energy-Efficient Wireless Telemonitoring of Noninvasive

Fetal ECG Via Block Sparse Bayesian Learning




Abstract: Fetal ECG (FECG) telemonitoring is an important branch in telemedicine. The design of a

telemonitoring system via a wireless body area network with low energy consumption for ambulatory use

is highly desirable. As an emerging technique, compressed sensing (CS) shows great promise in

compressing/reconstructing data with low energy consumption. However, due to some specific

characteristics of raw FECG recordings such as nonsparsity and strong noise contamination, current CS

algorithms generally fail in this application. This paper proposes to use the block sparse Bayesian learning

framework to compress/reconstruct nonsparse raw FECG recordings. Experimental results show that the

framework can reconstruct the raw recordings with high quality. Especially, the reconstruction does not

destroy the interdependence relation among the multichannel recordings. This ensures that the

independent component analysis decomposition of the reconstructed recordings has high fidelity.

Furthermore, the framework allows the use of a sparse binary sensing matrix with much fewer nonzero

entries to compress recordings. Particularly, each column of the matrix can contain only two nonzero

entries. This shows that the framework, compared to other algorithms such as current CS algorithms and

wavelet algorithms, can greatly reduce code execution in CPU in the data compression stage.

ETPL

BME-030 Clinical Validation of the Quick Dynamic Insulin Sensitivity Test

Abstract: The quick dynamic insulin sensitivity test (DISTq) can yield an insulin sensitivity result

immediately after a 30-min clinical protocol. The test uses intravenous boluses of 10 g glucose and 1 U

insulin at $t$ = 1 and 11 min, respectively, and measures glucose levels in samples taken at $t$ = 0, 10,

20, and 30 min. The low clinical cost of the protocol is enabled via robust model formulation and a series

of population-derived relationships that estimate insulin pharmacokinetics as a function of insulin

sensitivity ( SI). Fifty individuals underwent the gold standard euglycaemic clamp (EIC) and DISTq

within an eight-day period.SI values from the EIC and two DISTq variants (four-sample DISTq and two-

sample DISTq30) were compared with correlation, Bland–Altman and receiver operator curve analyses.

DISTq and DISTq30 correlated well with the EIC [$R$ = 0.76 and 0.75, and receiver operator curve c-

index = 0.84 and 0.85, respectively]. The median differences between EIC and DISTq/DISTq30 SI values

were 13% and 22%, respectively. The DISTq estimation method predicted individual insulin responses

without specific insulin assays with relative accuracy and thus high equivalence to EIC SI values was

achieved. DISTq produced very inexpensive, relatively accurate immediate results, and can thus enable a

number of applications that are impossible with established SI tests.

ETPL

BME-031 Spine Image Fusion Via Graph Cuts

Abstract: This study investigates a novel CT/MR spine image fusion algorithm based on graph cuts. This

algorithm allows physicians to visually assess corresponding soft tissue and bony detail on a single image

eliminating mental alignment and correlation needed when both CT and MR images are required for

diagnosis. We state the problem as a discrete multilabel optimization of an energy functional that balances

the contributions of three competing terms: (1) a squared error, which encourages the solution to be



http://www.elysiumtechnologies.com, [email protected] similar to the MR input, with a preference to strong MR edges; (2) a squared error, which encourages the

solution to be similar to the CT input, with a preference to strong CT edges; and (3) a prior, which favors

smooth solutions by encouraging neighboring pixels to have similar fused-image values. We further

introduce a transparency-labeling formulation, which significantly reduces the computational load. The

proposed graph-cut fusion guarantees nearly global solutions, while avoiding the pix elation artifacts that

affect standard wavelet-based methods. We report several quantitative evaluations/comparisons over 40

pairs of CT/MR images acquired from 20 patients, which demonstrate a very competitive performance in

comparisons to the existing methods. We further discuss various case studies, and give a representative

sample of the results.

ETPL

BME-032 Cross-Scale Coefficient Selection for Volumetric Medical Image Fusion

Abstract: Joint analysis of medical data collected from different imaging modalities has become a

common clinical practice. Therefore, image fusion techniques, which provide an efficient way of

combining and enhancing information, have drawn increasing attention from the medical community. In

this paper, we propose a novel cross-scale fusion rule for multiscale-decomposition-based fusion of

volumetric medical images taking into account both intrascale and interscale consistencies. An optimal set

of coefficients from the multiscale representations of the source images is determined by effective

exploitation of neighborhood information. An efficient color fusion scheme is also proposed. Experiments

demonstrate that our fusion rule generates better results than existing rules.

ETPL

BME-033 Estimation of Tool Pose Based on Force–Density Correlation During Robotic Drilling

Abstract: The application of image-guided systems with or without support by surgical robots relies on

the accuracy of the navigation process, including patient-to-image registration. The surgeon must carry

out the procedure based on the information provided by the navigation system, usually without being able

to verify its correctness beyond visual inspection. Misleading surrogate parameters such as the fiducial

registration error are often used to describe the success of the registration process, while a lack of

methods describing the effects of navigation errors, such as those caused by tracking or calibration, may

prevent the application of image guidance in certain accuracy-critical interventions. During minimally

invasive mastoidectomy for cochlear implantation, a direct tunnel is drilled from the outside of the

mastoid to a target on the cochlea based on registration using landmarks solely on the surface of the skull.

Using this methodology, it is impossible to detect if the drill is advancing in the correct direction and that

injury of the facial nerve will be avoided. To overcome this problem, a tool localization method based on

drilling process information is proposed. The algorithm estimates the pose of a robot-guided surgical tool

during a drilling task based on the correlation of the observed axial drilling force and the heterogeneous

bone density in the mastoid extracted from 3-D image data. We present here one possible implementation

of this method tested on ten tunnels drilled into three human cadaver specimens where an average tool

localization accuracy of 0.29 mm was observed.




ETPL

BME-034 Ephaptic Coupling in Cardiac Myocytes

Abstract: While it is widely believed that conduction in cardiac tissue is regulated by gap junctions, recent

experimental evidence suggests that the extracellular space may play a significant role in action potential

propagation. Cardiac tissue with low gap junctional coupling still exhibits conduction, with conflicting

degrees of slowing that may be due to variations in the extracellular space. Inhomogeneities in the

extracellular space caused by the complex cellular structure in cardiac tissue can lead to ephaptic, or field

effect, coupling. Here, we present data from simulations of a cylindrical strand of cells in which we see

the dramatic effect highly resistant extracellular spaces have on propagation velocity. We find that

ephaptic effects occur in all areas of small extracellular spaces and are not restricted to the junctional cleft

between cells. This previously unrecognized type of field coupling, which we call lateral coupling, can

allow conduction in the absence of gap junctions. We compare our results with the classically used cable

theory, demonstrating the quantitative difference in propagation velocity arising from the cellular

geometry. Ephaptic effects are shown to be highly dependent upon parameter values, frequently

enhancing, but sometimes decreasing propagation speed. Our mathematical analysis incorporates the

inhomogeneities in the extracellular microdomains that cannot be directly measured by experimental

techniques and will aid in optimizing cardiac treatments that require manipulation of the cellular

geometry and understanding heart functionality.

ETPL

BME-035 Raven-II: An Open Platform for Surgical Robotics Research

Abstract: The Raven-II is a platform for collaborative research on advances in surgical robotics. Seven

universities have begun research using this platform. The Raven-II system has two 3-DOF spherical

positioning mechanisms capable of attaching interchangeable four DOF instruments. The Raven-II

software is based on open standards such as Linux and ROS to maximally facilitate software

development. The mechanism is robust enough for repeated experiments and animal surgery experiments,

but is not engineered to sufficient safety standards for human use. Mechanisms in place for interaction

among the user community and dissemination of results include an electronic forum, an online software

SVN repository, and meetings and workshops at major robotics conferences.

ETPL

BME-036

Compressed Sensing of EEG for Wireless Telemonitoring With Low Energy

Consumption and Inexpensive Hardware

Abstract: Telemonitoring of electroencephalogram (EEG) through wireless body-area networks is an

evolving direction in personalized medicine. Among various constraints in designing such a system, three

important constraints are energy consumption, data compression, and device cost. Conventional data

compression methodologies, although effective in data compression, consumes significant energy and

cannot reduce device cost. Compressed sensing (CS), as an emerging data compression methodology, is

promising in catering to these constraints. However, EEG is nonsparse in the time domain and also

nonsparse in transformed domains (such as the wavelet domain). Therefore, it is extremely difficult for



http://www.elysiumtechnologies.com, [email protected] current CS algorithms to recover EEG with the quality that satisfies the requirements of clinical diagnosis

and engineering applications. Recently, block sparse Bayesian learning (BSBL) was proposed as a new

method to the CS problem. This study introduces the technique to the telemonitoring of EEG.

Experimental results show that its recovery quality is better than state-of-the-art CS algorithms, and

sufficient for practical use. These results suggest that BSBL is very promising for telemonitoring of EEG

and other nonsparse physiological signals.

ETPL

BME-037

The Alpha Band of the Resting Electroencephalogram Under Pulsed and Continuous

Radio Frequency Exposures

Abstract: The effect of GSM-like electromagnetic fields with the resting electroencephalogram (EEG)

alpha band activity was investigated in a double-blind cross-over experimental paradigm, testing the

hypothesis that pulsed but not continuous radio frequency (RF) exposure would affect alpha activity, and

the hypothesis that GSM-like pulsed low frequency fields would affect alpha. Seventy-two healthy

volunteers attended a single recording session where the eyes open resting EEG activity was recorded.

Four exposure intervals were presented (sham, pulsed modulated RF, continuous RF, and pulsed low

frequency) in a counterbalanced order where each exposure lasted for 20 min. Compared to sham, a

suppression of the global alpha band activity was observed under the pulsed modulated RF exposure, and

this did not differ from the continuous RF exposure. No effect was seen in the extremely low frequency

condition. That there was an effect of pulsed RF that did not differ significantly from continuous RF

exposure does not support the hypothesis that ―pulsed‖ RF is required to produce EEG effects. The results

support the view that alpha is altered by RF electromagnetic fields, but suggest that the pulsing nature of

the fields is not essential for this effect to occur.

ETPL

BME-038 A Wireless Robot for Networked Laparoscopy

Abstract: State-of-the-art laparoscopes for minimally invasive abdominal surgery are encumbered by

cabling for power, video, and light sources. Although these laparoscopes provide good image quality,

they interfere with surgical instruments, occupy a trocar port, require an assistant in the operating room to

control the scope, have a very limited field of view, and are expensive. MARVEL is a wireless Miniature

Anchored Robotic Videoscope for Expedited Laparoscopy that addresses these limitations by providing

an inexpensive in vivo wireless camera module (CM) that eliminates the surgical-tool bottleneck

experienced by surgeons in current laparoscopic endoscopic single-site (LESS) procedures. The

MARVEL system includes1) multiple CMs that feature awirelessly controlled pan/tilt camera platform,

which enable a full hemisphere field of view inside the abdominal cavity, wirelessly adjustable focus, and

a multiwavelength illumination control system; 2) a master control module that provides a near-zero

latency video wireless communications link, independent wireless control for multiple MARVEL CMs,

digital zoom; and 3) a wireless human-machine interface that gives the surgeon full control over CM

functionality. The research reported in this paper is the first step in developing a suite of semiautonomous

wirelessly controlled and networked robotic cyberphysical devices to enable a paradigm shift in



http://www.elysiumtechnologies.com, [email protected] minimally invasive surgery and other domains such as wireless body area networks.

ETPL

BME-039

Quantifying Limb Movements in Epileptic Seizures Through Color-Based Video

Analysis

Abstract: This paper proposes a color-based video analytic system for quantifying limb movements in

epileptic seizure monitoring. The system utilizes colored pyjamas to facilitate limb segmentation and

tracking. Thus, it is unobtrusive and requires no sensor/marker attached to patient's body. We employ

Gaussian mixture models in background/foreground modeling and detect limbs through a coarse-to-fine

paradigm with graph-cut-based segmentation. Next, we estimate limb parameters with domain knowledge

guidance and extract displacement and oscillation features from movement trajectories for seizure

detection/analysis. We report studies on sequences captured in an epilepsy monitoring unit. Experimental

evaluations show that the proposed system has achieved comparable performance to EEG-based systems

in detecting motor seizures.

ETPL

BME-040 Automatic Segmentation of Antenatal 3-D Ultrasound Images

Abstract: The development of 3-D ultrasonic probes and 3-D ultrasound (3DUS) imaging offers new

functionalities that call for specific image processing developments. In this paper, we propose an original

method for the segmentation of the utero-fetal unit (UFU) from 3DUS volumes, acquired during the first

trimester of gestation. UFU segmentation is required for a number of tasks, such as precise organ

delineation, 3-D modeling, quantitative measurements, and evaluation of the clinical impact of 3-D

imaging. The segmentation problem is formulated as the optimization of a partition of the image into two

classes of tissues: the amniotic fluid and the fetal tissues. A Bayesian formulation of the partition problem

integrates statistical models of the intensity distributions in each tissue class and regularity constraints on

the contours. An energy functional is minimized using a level set implementation of a deformable model

to identify the optimal partition. We propose to combine Rayleigh, Normal, Exponential, and Gamma

distribution models to compute the region homogeneity constraints. We tested the segmentation method

on a database of 19 antenatal 3DUS images. Promising results were obtained, showing the flexibility of

the level set formulation and the interest of learning the most appropriate statistical models according to

the idiosyncrasies of the data and the tissues. The segmentation method was shown to be robust to

different types of initialization and to provide accurate results, with an average overlap measure of 0.89

when comparing with manual segmentations.

ETPL

BME-041 Simultaneously Identifying All True Vessels From Segmented Retinal Images

Abstract: Measurements of retinal blood vessel morphology have been shown to be related to the risk of

cardiovascular diseases. The wrong identification of vessels may result in a large variation of these

measurements, leading to a wrong clinical diagnosis. In this paper, we address the problem of

automatically identifying true vessels as a postprocessing step to vascular structure segmentation. We



http://www.elysiumtechnologies.com, [email protected] model the segmented vascular structure as a vessel segment graph and formulate the problem of

identifying vessels as one of finding the optimal forest in the graph given a set of constraints. We design a

method to solve this optimization problem and evaluate it on a large real-world dataset of 2446 retinal

images. Experiment results are analyzed with respect to actual measurements of vessel morphology. The

results show that the proposed approach is able to achieve 98.9% pixel precision and 98.7% recall of the

true vessels for clean segmented retinal images, and remains robust even when the segmented image is

noisy.

ETPL

BME-042 Safety Auxiliary Feedback Element for the Artificial Pancreas in Type 1 Diabetes

Abstract: The artificial pancreas aims at the automatic delivery of insulin for glycemic control in patients

with type 1 diabetes, i.e., closed-loop glucose control. One of the challenges of the artificial pancreas is to

avoid controller overreaction leading to hypoglycemia, especially in the late postprandial period. In this

study, an original proposal based on sliding mode reference conditioning ideas is presented as a way to

reduce hypoglycemia events induced by a closed-loop glucose controller. The method is inspired in the

intuitive advantages of two-step constrained control algorithms. It acts on the glucose reference sent to the

main controller shaping it so as to avoid violating given constraints on the insulin-on-board. Some

distinctive features of the proposed strategy are that 1) it provides a safety layer which can be adjusted

according to medical criteria; 2) it can be added to closed-loop controllers of any nature; 3) it is robust

against sensor failures and overestimated prandial insulin doses; and 4) it can handle nonlinear models.

The method is evaluated in silico with the ten adult patients available in the FDA-accepted UVA

simulator.

ETPL

BME-043 Cuffless Differential Blood Pressure Estimation Using Smart Phones

Abstract: Smart phones today have become increasingly popular with the general public for their diverse

functionalities such as navigation, social networking, and multimedia facilities. These phones are

equipped with high-end processors, high-resolution cameras, and built-in sensors such as accelerometer,

orientation-sensor, and light-sensor. According to comScore survey, 26.2% of U.S. adults use smart

phones in their daily lives. Motivated by this statistic and the diverse capability of smart phones, we focus

on utilizing them for biomedical applications. We present a new application of the smart phone with its

built-in camera and microphone replacing the traditional stethoscope and cuff-based measurement

technique, to quantify vital signs such as heart rate and blood pressure. We propose two differential blood

pressure estimating techniques using the heartbeat and pulse data. The first method uses two smart phones

whereas the second method replaces one of the phones with a customized external microphone. We

estimate the systolic and diastolic pressure in the two techniques by computing the pulse pressure and the

stroke volume from the data recorded. By comparing the estimated blood pressure values with those

measured using a commercial blood pressure meter, we obtained encouraging results of 95-100%

accuracy.

ETPL

BME-044

Design and Implementation of a Wireless Capsule Suitable for Autofluorescence

Intensity Detection in Biological Tissues




Abstract: We report on the design, fabrication, testing, and packaging of a miniaturized system capable of

detecting autofluorescence (AF) from mammalian intestinal tissue. The system comprises an application-

specific integrated circuit (ASIC), light-emitting diode, optical filters, control unit, and radio transmitter.

The ASIC contains a high-voltage charge pump and single-photon avalanche diode detector (SPAD). The

charge pump biases the SPAD above its breakdown voltage to operate in Geiger mode. The SPAD offers

a photon detection efficiency of 37% at 520 nm, which corresponds to the AF emission peak of the

principle human intestinal fluorophore, flavin adenine dinucleotide. The ASIC was fabricated using a

commercial triple-well high-voltage CMOS process. The complete device operates at 3 V and draws an

average of 7.1 mA, enabling up to 23 h of continuous operation from two 165-mAh SR44 batteries.

ETPL

BME-045 A Dynamic Risk Score to Identify Increased Risk for Heart Failure Decompensation

Abstract: A method for combining heart failure (HF) diagnostic information in a Bayesian belief network

(BBN) framework to improve the ability to identify when patients are at risk for HF hospitalization

(HFH) is investigated in this paper. Implantable devices collect HF related diagnostics, such as

intrathoracic impedance, atrial fibrillation (AF) burden, ventricular rate during AF, night heart rate, heart

rate variability, and patient activity, on a daily basis. Features were extracted that encoded information

regarding out of normal range values as well as temporal changes at weekly and monthly time scales. A

BBN is used to combine the features to generate a risk score defined as the probability of a HFH given the

diagnostic evidence. Patients with a very high risk score at follow-up are 15 times more likely to have a

HFH in the next 30 days compared to patients with a low-risk score. The combined score has improved

ability to identify patients at risk for HFH compared to the individual diagnostic parameters. A score of

this nature allows clinicians to manage patients by exception; a patient with higher risk score needs more

attention than a patient with lower risk score.

ETPL

BME-046

Design and Optimization of Reaction Chamber and Detection System in Dynamic

Labs-on-Chip for Proteins Detection

Abstract: In this paper, the lab-on-chip section for a protein assay is designed and optimized. To avoid

severe reliability problems related to activated surface stability, a dynamic assay approach is adopted:

protein-to-protein neutralization is performed while proteins diffuse freely in the reaction chamber. The

related refraction index change is detected via an integrated interferometer. The structure is also design to

provide a functional test of the reference protein solution, which is generally required for qualification for

medical uses.

ETPL

BME-047

An Approach to Rapid Calculation of Temperature Change in Tissue Using Spatial

Filters to Approximate Effects of Thermal Conduction

Abstract: We present an approach to performing rapid calculations of temperature within tissue by

interleaving, at regular time intervals, 1) an analytical solution to the Pennes (or other desired) bioheat



http://www.elysiumtechnologies.com, [email protected] equation excluding the term for thermal conduction and 2) application of a spatial filter to approximate

the effects of thermal conduction. Here, the basic approach is presented with attention to filter design. The

method is applied to a few different cases relevant to magnetic resonance imaging, and results are

compared to those from a full finite-difference (FD) implementation of the Pennes bioheat equation. It is

seen that results of the proposed method are in reasonable agreement with those of the FD approach, with

about 15% difference in the calculated maximum temperature increase, but are calculated in a fraction of

the time, requiring less than 2% of the calculation time for the FD approach in the cases evaluated.

ETPL

BME-048 Noninvasive Biomagnetic Detection of Isolated Ischemic Bowel Segments

Abstract: The slow wave activity was measured in the magnetoenterogram (MENG) of normal porcine

subjects ( N = 5) with segmental intestinal ischemia. The correlation changes in enteric slow wave

activity were determined in MENG and serosal electromyograms (EMG). MENG recordings show

significant changes in the frequency and power distribution of enteric slow-wave signals during

segmental ischemia, and these changes agree with changes observed in the serosal EMG. There was a

high degree of correlation between the frequency of the electrical activity recorded in MENG and in

serosal EMG (r = 0.97). The percentage of power distributed in brady- and normoenteric frequency

ranges exhibited significant segmental ischemic changes. Our results suggest that noninvasive MENG

detects ischemic changes in isolated small bowel segments.

ETPL

BME-049

A New Strategy for Model Order Identification and Its Application to Transfer

Entropy for EEG Signals Analysis

Abstract: The background objective of this study is to analyze electrenocephalographic (EEG) signals

recorded with depth electrodes during seizures in patients with drug-resistant epilepsy. Usually, different

phases are observed during the seizure evolution, including a fast onset activity. We aim to ascertain how

cerebral structures get involved during this phase, in particular whether some structures ―drive‖ other

ones. Regarding a recent theoretical information measure, namely the transfer entropy (TE), we propose

two criteria, the first one is based on Akaike's information criterion, the second on the Bayesian

information criterion, to derive models’ orders that constitute crucial parameters in the TE estimation. A

normalized index, named partial transfer entropy (PTE), allows for quantifying the contribution or the

influence of a signal to the global information flow between a pair of signals. Experiments are first

conducted on linear autoregressive models, then on a physiology-based model, and finally on real

intracerebral EEG epileptic signals to detect and identify directions of causal interdependence. Results

support the relevance of the new measures for characterizing the information flow propagation whatever

unidirectional or bidirectional interactions.

ETPL

BME-050

Surface Electrocardiogram Reconstruction From Intracardiac Electrograms Using a

Dynamic Time Delay Artificial Neural Network

Abstract: This study proposes a method to facilitate the remote follow up of patients suffering from



http://www.elysiumtechnologies.com, [email protected] cardiac pathologies and treated with an implantable device, by synthesizing a 12-lead surface ECG from

the intracardiac electrograms (EGM) recorded by the device. Two methods (direct and indirect), based on

dynamic time-delay artificial neural networks (TDNNs) are proposed and compared with classical linear

approaches. The direct method aims to estimate 12 different transfer functions between the EGM and

each surface ECG signal. The indirect method is based on a preliminary orthogonalization phase of the

available EGM and ECG signals, and the application of the TDNN between these orthogonalized signals,

using only three transfer functions. These methods are evaluated on a dataset issued from 15 patients.

Correlation coefficients calculated between the synthesized and the real ECG show that the proposed

TDNN methods represent an efficient way to synthesize 12-lead ECG, from two or four EGM and

perform better than the linear ones. We also evaluate the results as a function of the EGM configuration.

Results are also supported by the comparison of extracted features and a qualitative analysis performed by

a cardiologist.

ETPL

BME-051 Segmentation of Dermoscopy Images Using Wavelet Networks

Abstract: This paper introduces a new approach for the segmentation of skin lesions in dermoscopic

images based on wavelet network (WN). The WN presented here is a member of fixed-grid WNs that is

formed with no need of training. In this WN, after formation of wavelet lattice, determining shift and

scale parameters of wavelets with two screening stage and selecting effective wavelets, orthogonal least

squares algorithm is used to calculate the network weights and to optimize the network structure. The

existence of two stages of screening increases globality of the wavelet lattice and provides a better

estimation of the function especially for larger scales. R, G, and B values of a dermoscopy image are

considered as the network inputs and the network structure formation. Then, the image is segmented and

the skin lesions exact boundary is determined accordingly. The segmentation algorithm were applied to

30 dermoscopic images and evaluated with 11 different metrics, using the segmentation result obtained by

a skilled pathologist as the ground truth. Experimental results show that our method acts more effectively

in comparison with some modern techniques that have been successfully used in many medical imaging

problems.

ETPL

BME-052

Prediction of Uterine Contractions Using Knowledge-Assisted Sequential Pattern

Analysis

Abstract: The usage of the systemic opioid remifentanil in relieving the labor pain has attracted much

attention recently. An optimal dosing regimen for administration of remifentanil during labor relies on

anticipating the timing of uterine contractions. These predictions should be made early enough to

maximize analgesia efficacy during contractions and minimize the impact of the medication between

contractions. We have designed a knowledge-assisted sequential pattern analysis framework to 1) predict

the intrauterine pressure in real time; 2) anticipate the next contraction; and 3) develop a sequential

association rule mining approach to identify the patterns of the contractions from historical patient

tracings (HT).




ETPL

BME-053

Development of a Wireless Sensor for the Measurement of Chicken Blood Flow Using

the Laser Doppler Blood Flow Meter Technique

Abstract: Here, we report the development of an integrated laser Doppler blood flow micrometer for

chickens. This sensor weighs only 18 g and is one of the smallest-sized blood flow meters, with no wired

line, these are features necessary for attaching the sensor to the chicken. The structure of the sensor chip

consists of two silicon cavities with a photo diode and a laser diode, which was achieved using the

microelectromechanical systems technique, resulting in its small size and significantly low power

consumption. In addition, we introduced an intermittent measuring arrangement in the measuring system

to reduce power consumption and to enable the sensor to work longer. We were successfully able to

measure chicken blood flow for five consecutive days, and discovered that chicken blood flow shows

daily fluctuations.

ETPL

BME-054

Validation of Statistical Channel Models for 60 GHz Radio Systems in Hospital

Environments

Abstract: Statistical channel models for $hbox{60}$ GHz communications systems in hospital

environments are validated using channel capacity and throughput of a physical layer as figures of merit.

The channel models are validated by comparing the performance figures with channels from the

measurements and the channel models. The throughput evaluation is based on system specifications given

by the IEEE 802.15.3 c standard for high data rate wireless personal area networks, namely orthogonal

frequency division multiplexing and single carrier transmissions. The channel capacity serves as a metric

of the potential of the two transmission schemes since it defines the upper bound of the throughput. The

capacity is derived based on the signal formats of the transmission schemes. The capacity shows that

$hbox{97}$ % of the measurement results are within $2sigma$ range of the modeled results. The

throughput shows that the channel models predict the maximum achievable throughput of the measured

channels precisely, while the mean throughput in some cases shows difference because of the

interpolation effect of the small-scale fading in the statistical channel models. Due to the interpolation

effect, the channel model is more suitable for a precise analysis of the outage performance than the

measurements where the number of channel samples is limited and the worst faded channels are not

necessarily included.

ETPL

BME-055 Multistructure Large Deformation Diffeomorphic Brain Registration

Abstract: Whole brain MRI registration has many useful applications in group analysis and morphometry,

yet accurate registration across different neuropathological groups remains challenging. Structure-specific

information, or anatomical guidance, can be used to initialize and constrain registration to improve

accuracy and robustness. We describe here a multistructure diffeomorphic registration approach that uses

concurrent subcortical and cortical shape matching to guide the overall registration. Validation

experiments carried out on openly available datasets demonstrate comparable or improved alignment of

subcortical and cortical brain structures over leading brain registration algorithms. We also demonstrate



http://www.elysiumtechnologies.com, [email protected] that a group-wise average atlas built with multistructure registration accounts for greater intersubject

variability and provides more sensitive tensor-based morphometry measurements

ETPL

BME-056 ECG Signal Quality During Arrhythmia and Its Application to False Alarm Reduction

Abstract: An automated algorithm to assess electrocardiogram (ECG) quality for both normal and

abnormal rhythms is presented for false arrhythmia alarm suppression of intensive care unit (ICU)

monitors. A particular focus is given to the quality assessment of a wide variety of arrhythmias. Data

from three databases were used: the Physionet Challenge 2011 dataset, the MIT-BIH arrhythmia database,

and the MIMIC II database. The quality of more than 33 000 single-lead 10 s ECG segments were

manually assessed and another 12 000 bad-quality single-lead ECG segments were generated using the

Physionet noise stress test database. Signal quality indices (SQIs) were derived from the ECGs segments

and used as the inputs to a support vector machine classifier with a Gaussian kernel. This classifier was

trained to estimate the quality of an ECG segment. Classification accuracies of up to 99% on the training

and test set were obtained for normal sinus rhythm and up to 95% for arrhythmias, although performance

varied greatly depending on the type of rhythm. Additionally, the association between 4050 ICU alarms

from the MIMIC II database and the signal quality, as evaluated by the classifier, was studied. Results

suggest that the SQIs should be rhythm specific and that the classifier should be trained for each rhythm

call independently. This would require a substantially increased set of labeled data in order to train an

accurate algorithm.

ETPL

BME-057

Tissue Classification Using Ultrasound-Induced Variations in Acoustic Backscattering

Features

Abstract: Ultrasound (US) radio-frequency (RF) time series is an effective tissue classification method

that enables accurate cancer diagnosis, but the mechanisms underlying this method are not completely

understood. This paper presents a model to describe the variations in tissue temperature and sound speed

that take place during the RF time series scanning procedures and relate these variations to US

backscattering. The model was used to derive four novel characterization features. These features were

used to classify three animal tissues, and they obtained accuracies as high as 88.01%. The performance of

the proposed features was compared with RF time series features proposed in a previous study. The

results indicated that the US-induced variations in tissue temperature and sound speed, which were used

to derive the proposed features, were important contributors to the tissue typing capabilities of the RF

time series. Simulations carried out to estimate the heating induced during the scanning procedure

employed in this study showed temperature rises lower than 2 °C. The model and results presented in this

paper can be used to improve the RF time series.

ETPL

BME-058

On-Chip Systolic Networks for Real-Time Tracking of Pairwise Correlations Between

Neurons in a Large-Scale Network

Abstract: The correlation map of neurons emerges as an important mathematical framework for a



http://www.elysiumtechnologies.com, [email protected] spectrum of applications including neural circuit modeling, neurologic disease bio-marking and

neuroimaging. However, constructing a correlation map is computationally expensive, especially when

the number of neurons is large. This paper proposes a hardware design using hierarchical systolic arrays

to calculate pairwise correlations between neurons. Through mapping a computationally efficient

algorithm for cross-correlation onto a massively parallel structure, the hardware is able to construct the

correlation maps in a much shorter time. The proposed architecture was evaluated using a field

programmable gate array. The results show that the computational delay of the hardware for constructing

correlation maps increases linearly with the number of neurons, whereas the growth of delay is quadratic

for a software-based serial approach. Also, the efficiency of our method for detecting abnormal behaviors

of neural circuits is demonstrated by analyzing correlation maps of retinal neurons.

ETPL

BME-059

An Online Failure Detection Method of the Glucose Sensor-Insulin Pump System:

Improved Overnight Safety of Type-1 Diabetic Subjects

Abstract: Sensors for real-time continuous glucose monitoring (CGM) and pumps for continuous

subcutaneous insulin infusion (CSII) have opened new scenarios for Type-1 diabetes treatment. However,

occasional failures of either CGM or CSII may expose diabetic patients to possibly severe risks,

especially overnight (e.g., inappropriate insulin administration). In this contribution, we present a method

to detect in real time such failures by simultaneously using CGM and CSII data streams and a black-box

model of the glucose-insulin system. First, an individualized state-space model of the glucose-insulin

system is identified offline from CGM and CSII data collected during a previous monitoring. Then, this

model, CGM and CSII real-time data streams are used online to obtain predictions of future glucose

concentrations together with their confidence intervals by exploiting a Kalman filtering approach. If

glucose values measured by the CGM sensor are not consistent with the predictions, a failure alert is

generated in order to mitigate the risks for patient safety. The method is tested on 100 virtual patients

created by using the UVA/Padova Type-1 diabetic simulator. Three different types of failures have been

simulated: spike in the CGM profile, loss of sensitivity of glucose sensor, and failure in the pump delivery

of insulin. Results show that, in all cases, the method is able to correctly generate alerts, with a very

limited number of false negatives and a number of false positives, on average, lower than 10%. The use of

the method in three subjects supports the simulation results, demonstrating that the accuracy of the

method in generating alerts in presence of failures of the CGM sensor-CSII pump system can

significantly improve safety of Type-1 diabetic patients overnight

ETPL

BME-060

Quantitative Evaluation of Transform Domains for Compressive Sampling-Based

Recovery of Sparsely Sampled Volumetric OCT Images

Abstract: Recently, compressive sampling has received significant attention as an emerging technique for

rapid volumetric imaging. We have previously investigated volumetric optical coherence tomography

(OCT) image acquisition using compressive sampling techniques and showed that it was possible to

recover image volumes from a subset of sampled images. Our previous findings used the

multidimensional wavelet transform as the domain of sparsification for recovering OCT image volumes.

In this report, we analyzed and compared the potential and efficiency of three other image transforms to



http://www.elysiumtechnologies.com, [email protected] reconstruct the same volumetric OCT image. Two quantitative measures, the mean square error and the

structural similarity index, were applied to compare the quality of the reconstructed volumetric images.

We observed that fast Fourier transformation and wavelet both are capable of reconstructing OCT image

volumes for the orthogonal sparse sampling masks used in this report, but with different merits.

ETPL

BME-061

The Use of a Bone-Anchored Device as a Hard-Wired Conduit for Transmitting EMG

Signals From Implanted Muscle Electrodes

Abstract: The use of a bone-anchored device to transmit electrical signals from internalized muscle

electrodes was studied in a sheep model. The bone-anchored device was used as a conduit for the passage

of a wire connecting an internal epimysial electrode to an external signal-recording device. The bone-

anchored device was inserted into an intact tibia and the electrode attached to the adjacent M. peroneus

tertius. ―Physiological‖ signals with low signal-to-noise ratios were successfully obtained over a 12-week

period by walking the sheep on a treadmill. Reliable transmission of multiple muscle signals across the

skin barrier is essential for providing intuitive, biomimetic upper limb prostheses. This technology has the

potential to provide a better functional and reliable solution for upper limb amputee rehabilitation:

attachment and control.

ETPL

BME-062

The iFit: An Integrated Physical Fitness Testing System to Evaluate the Degree of

Physical Fitness of the Elderly

Abstract: This paper presents an integrated physical fitness testing system (iFit) that evaluates the

physical fitness of older adults. The intent of the test is to help them manage and promote their health and

mitigate the effects of aging. National protocols of physical fitness were implemented to support the

assessment. The proposed system encompasses four modules of physical fitness assessment for both users

and medical professionals. The test information will be recorded and managed through a wireless sensor

network that will enable a better understanding of users' fitness states. Furthermore, the iFit has been

validated by a test session attended by elderly participants. The results show that there is a significant

correlation between iFit use in the test of flexibility, grip strength, and balance, compared to conventional

methods.

ETPL

BME-063

Multichannel Weighted Speech Classification System for Prediction of Major

Depression in Adolescents

Abstract: Early identification of adolescents at high imminent risk for clinical depression could

significantly reduce the burden of the disease. This study demonstrated that acoustic speech analysis and

classification can be used to determine early signs of major depression in adolescents, up to two years

before they meet clinical diagnostic criteria for the full-blown disorder. Individual contributions of four

different types of acoustic parameters [prosodic, glottal, Teager's energy operator (TEO), and spectral] to

depression-related changes of speech characteristics were examined. A new computational methodology

for the early prediction of depression in adolescents was developed and tested. The novel aspect of this

methodology is in the introduction of multichannel classification with a weighted decision procedure. It



http://www.elysiumtechnologies.com, [email protected] was observed that single-channel classification was effective in predicting depression with a desirable

specificity-to-sensitivity ratio and accuracy higher than chance level only when using glottal or prosodic

features. The best prediction performance was achieved with the new multichannel method, which used

four features (prosodic, glottal, TEO, and spectral). In the case of the person-based approach with two sets

of weights, the new multichannel method provided a high accuracy level of 73% and the sensitivity-to-

specificity ratio of 79%/67% for predicting future depression.

ETPL

BME-064

Improved Multimodality Data Fusion of Late Gadolinium Enhancement MRI to Left

Ventricular Voltage Maps in Ventricular Tachycardia Ablation

Abstract: Electroanatomical voltage mapping (EAVM) is commonly performed prior to catheter ablation

of scar-related ventricular tachycardia (VT) to locate the arrhythmic substrate and to guide the ablation

procedure. EAVM is used to locate the position of the ablation catheter and to provide a 3-D

reconstruction of left-ventricular anatomy and scar. However, EAVM measurements only represent the

endocardial scar with no transmural or epicardial information. Furthermore, EAVM is a time-consuming

procedure, with a high operator dependence and has low sampling density, i.e., spatial resolution. Late

gadolinium enhancement (LGE) magnetic resonance imaging (MRI) allows noninvasive assessment of

scar morphology that can depict 3-D scar architecture. Despite the potential use of LGE as a roadmap for

VT ablation for identification of arrhythmogenic substrate, its utility has been very limited. To allow for

identification of VT substrate, a correlation is needed between the substrates identified by EAVM as the

gold standard and LGE-MRI scar characteristics. To do so, a system must be developed to fuse the

datasets from these modalities. In this study, a registration pipeline for the fusion of LGE-MRI and

EAVM data is presented. A novel surface registration algorithm is proposed, integrating the matching of

global scar areas as an additional constraint in the registration process. A preparatory landmark

registration is initially performed to expedite the convergence of the algorithm. Numerical simulations

were performed to evaluate the accuracy of the registration in the presence of errors in identifying

landmarks in EAVM or LGE-MRI datasets as well as additional errors due to respiratory or cardiac

motion. Subsequently, the accuracy of the proposed fusion system was evaluated in a cohort of ten

patients undergoing VT ablation where both EAVM and LGE-MRI data were available. Compared to

landmark registration and surface registration, the presented method achieved significant improvemen- in

registration error. The proposed data fusion system allows the fusion of EAVM and LGE-MRI data in VT

ablation with registration errors less than 3.5 mm.

ETPL

BME-065 A Navigation Platform for Guidance of Beating Heart Transapical Mitral Valve Repair

Abstract: Traditional surgical approaches for repairing diseased mitral valves (MVs) have relied on

placing the patient on cardiopulmonary bypass (on pump), stopping the heart and accessing the arrested

heart directly. However, because this approach has the potential for adverse neurological, vascular, and

immunological sequelae, less invasive beating heart alternatives are desirable. Emerging beating heart

techniques have been developed to offer high-risk patients MV repair using ultrasound guidance alone

without stopping the heart. This paper describes the first porcine trials of the NeoChord DS1000



http://www.elysiumtechnologies.com, [email protected] (Minnetonka, MN), employed to attach neochordae to a MV leaflet using the traditional ultrasound-

guided protocol augmented by dynamic virtual geometric models. The distance errors of the tracked tool

tip from the intended midline trajectory (5.2 ± 2.4 mm versus 16.8 ± 10.9 mm, p = 0.003), navigation

times (16.7 ± 8.0 s versus 92.0 ± 84.5 s, p = 0.004), and total path lengths (225.2 ± 120.3 mm versus

1128.9 ± 931.1 mm, p = 0.003) were significantly shorter in the augmented ultrasound compared to

navigation with ultrasound alone,1 indicating a substantial improvement in the safety and simplicity of

the procedure.

ETPL

BME-066

A Wideband Dual-Antenna Receiver for Wireless Recording From Animals Behaving

in Large Arenas

Abstract: A low-noise wideband receiver (Rx) is presented for a multichannel wireless implantable neural

recording (WINeR) system that utilizes time-division multiplexing of pulse width modulated (PWM)

samples. The WINeR-6 Rx consists of four parts: 1) RF front end; 2) signal conditioning; 3) analog

output (AO); and 4) field-programmable gate array (FPGA) back end. The RF front end receives RF-

modulated neural signals in the 403-490 MHz band with a wide bandwidth of 18 MHz. The frequency-

shift keying (FSK) PWM demodulator in the FPGA is a time-to-digital converter with 304 ps resolution,

which converts the analog pulse width information to 16-bit digital samples. Automated frequency

tracking has been implemented in the Rx to lock onto the free-running voltage-controlled oscillator in the

transmitter (Tx). Two antennas and two parallel RF paths are used to increase the wireless coverage area.

BCI-2000 graphical user interface has been adopted and modified to acquire, visualize, and record the

recovered neural signals in real time. The AO module picks three demultiplexed channels and converts

them into analog signals for direct observation on an oscilloscope. One of these signals is further

amplified to generate an audio output, offering users the ability to listen to ongoing neural activity.

Bench-top testing of the Rx performance with a 32-channel WINeR-6 Tx showed that the input referred

noise of the entire system at a Tx-Rx distance of 1.5 m was 4.58 μVrms with 8-bit resolution at 640 kSps.

In an in vivo experiment, location-specific receptive fields of hippocampal place cells were mapped

during a behavioral experiment in which a rat completed 40 laps in a large circular track. Results were

compared against those acquired from the same animal and the same set of electrodes by a commercial

hardwired recording system to validate the wirelessly recorded signals.

ETPL

BME-067 iBalance-ABF: A Smartphone-Based Audio-Biofeedback Balance System

Abstract: This paper proposes an implementation of a Kalman filter, using inertial sensors of a

smartphone, to estimate 3-D angulation of the trunk. The developed system monitors the trunk angular

evolution during bipedal stance and helps the user to improve balance through a configurable and

integrated auditory-biofeedback (ABF) loop. A proof-of-concept study was performed to assess the

effectiveness of this so-called iBalance-ABF-smartphone-based audio-biofeedback system-in improving

balance during bipedal standing. Results showed that young healthy individuals were able to efficiently

use ABF on sagittal trunk tilt to improve their balance in the medial-lateral direction. These findings

suggest that the iBalance-ABF system as a telerehabilitation system could represent a suitable solution for



http://www.elysiumtechnologies.com, [email protected] ambient assisted living technologies.

ETPL

BME-068

A Reconfigurable Digital Filterbank for Hearing-Aid Systems With a Variety of Sound

Wave Decomposition Plans

Abstract: Current hearing-aid systems have fixed sound wave decomposition plans due to the use of fixed

filterbanks, thus cannot provide enough flexibility for the compensation of different hearing impairment

cases. In this paper, a reconfigurable filterbank that consists of a multiband-generation block and a

subband-selection block is proposed. Different subbands can be produced according to the control

parameters without changing the structure of the filterbank system. The use of interpolation, decimation,

and frequency-response masking enables us to reduce the computational complexity by realizing the

entire system with only three prototype filters. Reconfigurability of the proposed filterbank enables

hearing-impaired people to customize hearing aids based on their own specific conditions to improve their

hearing ability. We show, by means of examples, that the proposed filterbank can achieve a better

matching to the audiogram and has smaller complexity compared with the fixed filterbank. The drawback

of the proposed method is that the throughput delay is relatively long (>20 ms), which needs to be further

reduced before it can be used in a real hearing-aid application.

ETPL

BME-069

A Fully Constrained Optimization Method for Time-Resolved Multispectral

Fluorescence Lifetime Imaging Microscopy Data Unmixing

Abstract: This paper presents a new unmixing methodology of multispectral fluorescence lifetime

imaging microscopy (m-FLIM) data, in which the spectrum is defined as the combination of time-domain

fluorescence decays at multiple emission wavelengths. The method is based on a quadratic constrained

optimization (CO) algorithm that provides a closed-form solution under equality and inequality

restrictions. In this paper, it is assumed that the time-resolved fluorescence spectrum profiles of the

constituent components are linearly independent and known a priori. For comparison purposes, the

standard least squares (LS) solution and two constrained versions nonnegativity constrained least squares

(NCLS) and fully constrained least squares (FCLS) (Heinz and Chang, 2001) are also tested. Their

performance was evaluated by using synthetic simulations, as well as imaged samples from fluorescent

dyes and ex vivo tissue. In all the synthetic evaluations, the CO obtained the best accuracy in the

estimations of the proportional contributions. CO could achieve an improvement ranging between 41%

and 59% in the relative error compared to LS, NCLS, and FCLS at different signal-to-noise ratios. A

liquid mixture of fluorescent dyes was also prepared and imaged in order to provide a controlled scenario

with real data, where CO and FCLS obtained the best performance. The CO and FCLS were also tested

with 20 ex vivo samples of human coronary arteries, where the expected concentrations are qualitatively

known. A certainty measure was employed to assess the confidence in the estimations made by each

algorithm. The experiments confirmed a better performance of CO, since this method is optimal with

respect to equality and inequality restrictions in the linear unmixing formulation. Thus, the evaluation

showed that CO achieves an accurate characterization of the samples. Furthermore, CO is a computational

efficient alternative to estimate the abundance of components in m-FLIM data, since a global optima-



http://www.elysiumtechnologies.com, [email protected] solution is always guaranteed in a closed form.

ETPL

BME-070 An Integrated μLED Optrode for Optogenetic Stimulation and Electrical Recording

Abstract: In this letter, we developed an integrated neural probe prototype for optogenetic stimulation by

microscale light-emitting diode (μLED) and simultaneous recording of neural activities with

microelectrodes on a single-polyimide platform. Optogenetics stimulates in vivo neural circuits with high-

cellular specificity achieved by genetic targeting and precise temporal resolution by interaction of light-

gated ion channels with optical beam. In our newly developed optrode probe, during optogenetic

stimulation of neurons, continuous sensing of neuronal activities in vicinity of the activation site can

provide feedback to stimulation or examine local responses in signal pathways. In the device, focusing the

light from the μLED was achieved with an integrated photo-polymerized lens. The efficacy of the optrode

for cortical stimulation and recording was tested on mice visual cortex neurons expressing

channelrhodopsin-2. Stimulation intensity and frequency-dependent spiking activities of visual cortex

were recorded. Our device has shown advantages over fiber-coupled laser-based optrode in terms of

closed-loop integration, single-implant compactness and lower electrical power requirements, which

would be clinically applicable for future prosthetic applications in personalized medicine.

ETPL

BME-071

Electrosurgical Vessel Sealing Tissue Temperature: Experimental Measurement and

Finite Element Modeling

Abstract: The temporal and spatial tissue temperature profile in electrosurgical vessel sealing was

experimentally measured and modeled using finite element modeling (FEM). Vessel sealing procedures

are often performed near the neurovascular bundle and may cause collateral neural thermal damage.

Therefore, the heat generated during electrosurgical vessel sealing is of concern among surgeons. Tissue

temperature in an in vivo porcine femoral artery sealed using a bipolar electrosurgical device was studied.

Three FEM techniques were incorporated to model the tissue evaporation, water loss, and fusion by

manipulating the specific heat, electrical conductivity, and electrical contact resistance, respectively.

These three techniques enable the FEM to accurately predict the vessel sealing tissue temperature profile.

The averaged discrepancy between the experimentally measured temperature and the FEM predicted

temperature at three thermistor locations is less than 7%. The maximum error is 23.9%. Effects of the

three FEM techniques are also quantified.

ETPL

BME-072

Debye Parameter Extraction for Characterizing Interaction of Terahertz Radiation

With Human Skin Tissue

Abstract: This paper is concerned with parameter extraction for the double Debye model, which is used

for analytically determining human skin permittivity. These parameters are thought to be the origin of

contrast in terahertz (THz) images of skin cancer. The existing extraction methods could generate Debye

models, which track their measurements accurately at frequencies higher than 1 THz but poorly at lower

frequencies, where the majority of permittivity contrast between healthy and diseased skin tissues is



http://www.elysiumtechnologies.com, [email protected] actually observed. We propose a global optimization-based parameter extraction, which results in globally

accurate tracking and thus supports the full validity of the Debye model for simulating human skin

permittivity in the whole usable THz frequencies. Numerical results confirm viability of our novel

methodology.

ETPL

BME-073

Coefficient-Free Blood Pressure Estimation Based on Pulse Transit Time–Cuff

Pressure Dependence

Abstract: Oscillometry is a popular technique for automatic estimation of blood pressure (BP). However,

most of the oscillometric algorithms rely on empirical coefficients for systolic and diastolic pressure

evaluation that may differ in various patient populations, rendering the technique unreliable. A promising

complementary technique for automatic estimation of BP, based on the dependence of pulse transit time

(PTT) on cuff pressure (CP) (PTT-CP mapping), has been proposed in the literature. However, a

theoretical grounding for this technique and a nonparametric BP estimation approach are still missing. In

this paper, we propose a novel coefficient-free BP estimation method based on PTT-CP dependence. PTT

is mathematically modeled as a function of arterial lumen area under the cuff. It is then analytically

shown that PTT-CP mappings computed from various points on the arterial pulses can be used to directly

estimate systolic, diastolic, and mean arterial pressure without empirical coefficients. Analytical results

are cross-validated with a pilot investigation on ten healthy subjects where 150 simultaneous

electrocardiogram and oscillometric BP recordings are analyzed. The results are encouraging whereby the

mean absolute errors of the proposed method in estimating systolic and diastolic pressures are 5.31 and

4.51 mmHg, respectively, relative to the Food and Drug Administration approved Omron monitor. Our

work thus shows promise toward providing robust and objective BP estimation in a variety of patients and

monitoring situations.

ETPL

BME-074

Ontology for Heart Rate Turbulence Domain From The Conceptual Model of

SNOMED-CT

Abstract: Electronic health record (EHR) automates the clinician workflow, allowing evidence-based

decision support and quality management. We aimed to start a framework for domain standardization of

cardiovascular risk stratification into the EHR, including risk indices whose calculation involves ECG

signal processing. We propose the use of biomedical ontologies completely based on the conceptual

model of SNOMED-CT, which allows us to implement our domain in the EHR. In this setting, the

present study focused on the heart rate turbulence (HRT) domain, according to its concise guidelines and

clear procedures for parameter calculations. We used 289 concepts from SNOMED-CT, and generated 19

local extensions (new concepts) for the HRT specific concepts not present in the current version of

SNOMED-CT. New concepts included averaged and individual ventricular premature complex

tachograms, initial sinus acceleration for turbulence onset, or sinusal oscillation for turbulence slope. Two

representative use studies were implemented: first, a prototype was inserted in the hospital information

system for supporting HRT recordings and their simple follow up by medical societies; second, an

advanced support for a prospective scientific research, involving standard and emergent signal processing

algorithms in the HRT indices, was generated and then tested in an example database of 27 Holter

patients. Concepts of the proposed HRT ontology are publicly available through a terminology server,



http://www.elysiumtechnologies.com, [email protected] hence their use in any information system will be straightforward due to the interoperability provided by

SNOMED-CT.

ETPL

BME-075

Dynamical Nonstationarity of Resting EEGs in Patients With Attention-

Deficit/Hyperactivity Disorder (AD/HD)

Abstract: This study applied dynamical nonstationarity analysis (DNA) to the resting EEGs of patients

with attention-deficit/hyperactivity disorder (AD/HD). We aimed to assess and characterize AD/HD using

features based on the local and global duration of dynamical microstate. We hypothesized that AD/HD

patients would have difficulties in maintaining stable cognitive states (e.g., attention deficit and

impulsivity) and that they would thus exhibit EEGs with temporal dynamics distinct from normal

controls, i.e., rapidly and frequently changing dynamics. To test this hypothesis, we recorded EEGs from

12 adolescent subjects with AD/HD and 11 age-matched healthy subjects in the resting state with eyes

closed and eyes open. We found that AD/HD patients exhibited significantly faster changes in dynamics

than controls in the right temporal region during the eyes closed condition, but slower changes in

dynamics in the frontal region during the eyes open condition. AD/HD patients exhibited a disruption in

the rate of change of dynamics in the frontotemporal region at rest, probably due to executive and

attention processes. We suggest that the DNA using complementary local and global features based on the

duration of dynamical microstates could be a useful tool for the clinical diagnosis of subjects with

AD/HD.

ETPL

BME-076 Classification and Staging of Chronic Liver Disease From Multimodal Data

Abstract: Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately

potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound

images, laboratory tests, and clinical records are described. The first stage of the proposed method, called

clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy

conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical

basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used

as well as the classifiers (Bayes, Parzen, support vector machine, and $k$ -nearest neighbor) are optimally

selected for each stage. A large multimodal feature database was specifically built for this study

containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis

cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme

outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the

normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector.

ETPL

BME-077

The Use of Ensemble Empirical Mode Decomposition With Canonical Correlation

Analysis as a Novel Artifact Removal Technique

Abstract: Biosignal measurement and processing is increasingly being deployed in ambulatory situations

particularly in connected health applications. Such an environment dramatically increases the likelihood

of artifacts which can occlude features of interest and reduce the quality of information available in the



http://www.elysiumtechnologies.com, [email protected] signal. If multichannel recordings are available for a given signal source, then there are currently a

considerable range of methods which can suppress or in some cases remove the distorting effect of such

artifacts. There are, however, considerably fewer techniques available if only a single-channel

measurement is available and yet single-channel measurements are important where minimal

instrumentation complexity is required. This paper describes a novel artifact removal technique for use in

such a context. The technique known as ensemble empirical mode decomposition with canonical

correlation analysis (EEMD-CCA) is capable of operating on single-channel measurements. The EEMD

technique is first used to decompose the single-channel signal into a multidimensional signal. The CCA

technique is then employed to isolate the artifact components from the underlying signal using second-

order statistics. The new technique is tested against the currently available wavelet denoising and EEMD-

ICA techniques using both electroencephalography and functional near-infrared spectroscopy data and is

shown to produce significantly improved results.

ETPL

BME-078

Smart Anesthesia Manager ^{\rm TM} (SAM)—A Real-time Decision Support System

for Anesthesia Care during Surgery

Abstract: Anesthesia information management systems (AIMS) are being increasingly used in the

operating room to document anesthesia care. We developed a system, Smart Anesthesia ManagerTM

(SAM) that works in conjunction with an AIMS to provide clinical and billing decision support. SAM

interrogates AIMS database in near real time, detects issues related to clinical care, billing and

compliance, and material waste. Issues and the steps for their resolution are brought to the attention of the

anesthesia provider in real time through ―pop-up‖ messages overlaid on top of AIMS screens or text

pages. SAM improved compliance to antibiotic initial dose and redose to 99.3 ± 0.7% and 83.9 ± 3.4%

from 88.5 ± 1.4% and 62.5 ± 1.6%, respectively. Beta-blocker protocol compliance increased to 94.6 ±

3.5% from 60.5 ± 8.6%. Inadvertent gaps (>;15 min) in blood pressure monitoring were reduced to 34 ±

30 min/1000 cases from 192 ± 58 min/1000 cases. Additional billing charge capture of invasive lines

procedures worth $144,732 per year and 1,200 compliant records were achieved with SAM. SAM was

also able to reduce wastage of inhalation anesthetic agents worth $120,168 per year.

ETPL

BME-079

High-Accuracy Patient-to-Image Registration for the Facilitation of Image-Guided

Robotic Microsurgery on the Head

Abstract: Image-guided microsurgery requires accuracies an order of magnitude higher than today's

navigation systems provide. A critical step toward the achievement of such low-error requirements is a

highly accurate and verified patient-to-image registration. With the aim of reducing target registration

error to a level that would facilitate the use of image-guided robotic microsurgery on the rigid anatomy of

the head, we have developed a semiautomatic fiducial detection technique. Automatic force-controlled

localization of fiducials on the patient is achieved through the implementation of a robotic-controlled

tactile search within the head of a standard surgical screw. Precise detection of the corresponding

fiducials in the image data is realized using an automated model-based matching algorithm on high-

resolution, isometric cone beam CT images. Verification of the registration technique on phantoms

demonstrated that through the elimination of user variability, clinically relevant target registration errors

of approximately 0.1 mm could be achieved.




ETPL

BME-080

Biologically Derived Companding Algorithm for High Dynamic Range Mammography

Images

Abstract: The screening mammography is currently the best procedure available for early detection of the

breast cancer. The acquired mammograms are high dynamic range (HDR) images having a 12 bit

grayscale resolution. When viewed by a radiologist, a single image must be examined several times, each

time focusing on a different intensity range. We have developed a biologically derived mammography

companding (BDMC) algorithm for compression, expansion, and enhancement of mammograms, in a

fully automatic way. The BDMC is comprised of two main processing stages: 1) preliminary processing

operations which include standardization of the intensity range and expansion of the intensities which

belong to the low intensity range. 2) Adaptively companding the HDR range by integrating multiscale

contrast measures. The algorithm's performance has been preliminarily clinically tested on dozens of

mammograms in collaboration with experienced radiologists. It appears that the suggested method

succeeds in presenting all of the clinical information, including all the abnormalities, in a single low

dynamic range companded image. This companded and enhanced image is not degraded more than the

HDR image and can be analyzed without the need for professional workstation and its specific

enhancement software.

ETPL

BME-081

Advantages and Limitations of Using Matrix Pencil Method for the Modal Analysis of

Medical Percussion Signals

Abstract: Although clinical percussion remains one of the most widespread traditional noninvasive

methods for diagnosing pulmonary disease, the available analysis of physical characteristics of the

percussion sound using modern signal processing techniques is still quite limited. The majority of existing

literature on the subject reports either time-domain or spectral analysis methods. However, Fourier

analysis, which represents the signal as a sum of infinite periodic harmonics, is not naturally suited for

decomposition of short and aperiodic percussion signals. Broadening of the spectral peaks due to damping

leads to their overlapping and masking of the lower amplitude peaks, which could be important for the

fine-level signal classification. In this study, an attempt is made to automatically decompose percussion

signals into a sum of exponentially damped harmonics, which in this case form a more natural basis than

Fourier harmonics and thus allow for a more robust representation of the signal in the parametric space.

The damped harmonic decomposition of percussion signals recorded on healthy volunteers in clinical

setting is performed using the matrix pencil method, which proves to be quite robust in the presence of

noise and well suited for the task.

ETPL

BME-082

A Fast CT and CT-Fluoroscopy Registration Algorithm With Respiratory Motion

Compensation for Image-Guided Lung Intervention

Abstract: CT-fluoroscopy (CTF) is an efficient imaging technique for guiding percutaneous lung

intervention such as biopsy and ablation. In CTF-guided procedures, four to ten axial images are captured

in a very short time period during breath holding to provide near real-time feedback of patients' anatomy

so that physicians can adjust the needle as it is advanced toward a target lesion. Although popularly used



http://www.elysiumtechnologies.com, [email protected] in clinics, this procedure requires frequent scans to guide the needle, which may cause increased

procedure time, complication rates, and radiation exposure to both clinicians and patients. In addition,

CTF only generates a limited number of 2-D axial images and does not provide sufficient 3-D anatomical

information. Therefore, how to provide volumetric anatomical information using CTF while reducing

intraoperative scan is an important and challenging problem. In this paper, we propose a fast CT-CTF

deformable registration algorithm that warps the inhale preprocedural CT onto the intraprocedural CTF

for guidance in 3-D. In the algorithm, the deformation in the transverse plane is modeled using 2-D B-

Spline, and the deformation along z-direction is regularized by smoothness constraint. A respiratory

motion compensation framework is also incorporated for accurate registration. A parallel implementation

strategy is adopted to accomplish the registration in several seconds. With electromagnetic tracking, the

needle position can be superimposed onto the deformed inhale CT image, thereby providing 3-D image

guidance during breath holding. Experiments were conducted using both simulated CTF images with

known deformation and real CTF images captured during lung cancer biopsy studies. The experiments

demonstrated satisfactory registration results of our proposed fast CT-CTF registration algorithm.

ETPL

BME-083

Impact of Visual Features on the Segmentation of Gastroenterology Images Using

Normalized Cuts

Abstract: Gastroenterology imaging is an essential tool to detect gastrointestinal cancer in patients.

Computer-assisted diagnosis is desirable to help us improve the reliability of this detection. However,

traditional computer vision methodologies, mainly segmentation, do not translate well to the specific

visual characteristics of a gastroenterology imaging scenario. In this paper, we propose a novel method

for the segmentation of gastroenterology images from two distinct imaging modalities and organs:

chromoendoscopy (CH) and narrow-band imaging (NBI) from stomach and esophagus, respectively. We

have used various visual features individually and their combinations (edgemaps, creaseness, and color)

in normalized cuts image segmentation framework to segment ground truth datasets of 142 CH and 224

NBI images. Experiments show that an integration of edgemaps and creaseness in normalized cuts gives

the best segmentation performance resulting in high-quality segmentations of the gastroenterology

images.

ETPL

BME-084 Objective Skill Evaluation for Laparoscopic Training Based on Motion Analysis

Abstract: Performing laparoscopic surgery requires several skills, which have never been required for

conventional open surgery. Surgeons experience difficulties in learning and mastering these techniques.

Various training methods and metrics have been developed to assess and improve surgeon's operative

abilities. While these training metrics are currently widely being used, skill evaluation methods are still

far from being objective in the regular laparoscopic skill education. This study proposes a methodology of

defining a processing model that objectively evaluates surgical movement performance in the routine

laparoscopic training course. Our approach is based on the analysis of kinematic data describing the

movements of surgeon's upper limbs. An ultraminiaturized wearable motion capture system (Waseda

Bioinstrumentation system WB-3), therefore, has been developed to measure and analyze these



http://www.elysiumtechnologies.com, [email protected] movements. The data processing model was trained by using the subjects' motion features acquired from

the WB-3 system and further validated to classify the expertise levels of the subjects with different

laparoscopic experience. Experimental results show that the proposed methodology can be efficiently

used both for quantitative assessment of surgical movement performance, and for the discrimination

between expert surgeons and novices.

ETPL

BME-085

Feature-Preserving Smoothing of Diffusion Weighted Images Using Nonstationarity

Adaptive Filtering

Abstract: Although promising for studying the microstructure of in vivo tissues, the performance and the

potentiality of diffusion tensor magnetic resonance imaging are hampered by the presence of high-level

noise in diffusion weighted (DW) images. This paper proposes a novel smoothing approach, called the

nonstationarity adaptive filtering, which estimates the intensity of a pixel by averaging intensities in its

adaptive homogeneous neighborhood. The latter is determined according to five constraints and

spatiodirectional nonstationarity measure maps. The proposed approach is compared with an anisotropic

diffusion method used in DW image smoothing. Experimental results on both synthetic and real human

DW images show that the proposed method achieves a better compromise between the smoothness of

homogeneous regions and the preservation of desirable features such as boundaries, even for highly noisy

data, thus leading to homogeneously consistent tensor fields and consequently more coherent fibers.

ETPL

BME-086

Sparse Reconstruction of Breast MRI Using Homotopic L_0 Minimization in a

Regional Sparsified Domain

Abstract: The use of MRI for early breast examination and screening of asymptomatic women has

become increasing popular, given its ability to provide detailed tissue characteristics that cannot be

obtained using other imaging modalities such as mammography and ultrasound. Recent application-

oriented developments in compressed sensing theory have shown that certain types of magnetic resonance

images are inherently sparse in particular transform domains, and as such can be reconstructed with a

high level of accuracy from highly undersampled k-space data below Nyquist sampling rates using

homotopic L0 minimization schemes, which holds great potential for significantly reducing acquisition

time. An important consideration in the use of such homotopic L0 minimization schemes is the choice of

sparsifying transform. In this paper, a regional differential sparsifying transform is investigated for use

within a homotopic L0 minimization framework for reconstructing breast MRI. By taking local regional

characteristics into account, the regional differential sparsifying transform can better account for signal

variations and fine details that are characteristic of breast MRI than the popular finite differential

transform, while still maintaining strong structure fidelity. Experimental results show that good breast

MRI reconstruction accuracy can be achieved compared to existing methods.

ETPL

BME-087

On-Shoe Wearable Sensors for Gait and Turning Assessment of Patients With

Parkinson's Disease

Abstract: Assessment of locomotion through simple tests such as timed up and go (TUG) or walking trials



http://www.elysiumtechnologies.com, [email protected] can provide valuable information for the evaluation of treatment and the early diagnosis of people with

Parkinson's disease (PD). Common methods used in clinics are either based on complex motion

laboratory settings or simple timing outcomes using stop watches. The goal of this paper is to present an

innovative technology based on wearable sensors on-shoe and processing algorithm, which provides

outcome measures characterizing PD motor symptoms during TUG and gait tests. Our results on ten PD

patients and ten age-matched elderly subjects indicate an accuracy ± precision of 2.8 ± 2.4 cm/s and 1.3 ±

3.0 cm for stride velocity and stride length estimation compared to optical motion capture, with the

advantage of being practical to use in home or clinics without any discomfort for the subject. In addition,

the use of novel spatio-temporal parameters, including turning, swing width, path length, and their

intercycle variability, was also validated and showed interesting tendencies for discriminating patients in

ON and OFF states and control subjects.

ETPL

BME-088

Photon Efficiency Optimization in Time-Correlated Single Photon Counting Technique

for Fluorescence Lifetime Imaging Systems

Abstract: In time-correlated single photon counting (TCSPC) systems, the maximum signal throughput is

limited by the occurrence of pile-up and other effects. In many biological applications that exhibit high

levels of fluorescence intensity (FI), pile-up-related distortions yield serious distortions in the

fluorescence lifetime (FLT) calculation as well as significant decrease in the signal-to-noise ratio (SNR).

Recent developments that allow the use of high-repetition-rate light sources (in the range of 50-100 MHz)

in fluorescence lifetime imaging (FLIM) experiments enable minimization of pile-up-related distortions.

However, modern TCSPC configurations that use high-repetition-rate excitation sources for FLIM suffer

from dead-time-related distortions that cause unpredictable distortions of the FI signal. In this study, the

loss of SNR is described by F- value as it is typically done in FLIM systems. This F-value describes the

relation of the relative standard deviation in the estimated FLT to the relative standard deviation in FI

measurements. Optimization of the F-value allows minimization of signal distortion, as well as shortening

of the acquisition time for certain samples. We applied this method for Fluorescein, Rhodamine B, and

Erythrosine fluorescent solutions that have different FLT values (4 ns, 1.67 ns, and 140 ps, respectively).

ETPL

BME-089

Matching Pursuit and Source Deflation for Sparse EEG/MEG Dipole Moment

Estimation

Abstract: In this paper, we propose novel matching pursuit (MP)-based algorithms for EEG/MEG dipole

source localization and parameter estimation for multiple measurement vectors with constant sparsity.

The algorithms combine the ideas of MP for sparse signal recovery and source deflation, as employed in

estimation via alternating projections. The source-deflated matching pursuit (SDMP) approach mitigates

the problem of residual interference inherent in sequential MP-based methods or recursively applied

(RAP)-MUSIC. Furthermore, unlike prior methods based on alternating projection, SDMP allows one to

efficiently estimate the dipole orientation in addition to its location. Simulations show that the proposed

algorithms outperform existing techniques under various conditions, including those with highly

correlated sources. Results using real EEG data from auditory experiments are also presented to illustrate



http://www.elysiumtechnologies.com, [email protected] the performance of these algorithms.

ETPL

BME-090 Multiparameter Respiratory Rate Estimation From the Photoplethysmogram

Abstract: We present a novel method for estimating respiratory rate in real time from the

photoplethysmogram (PPG) obtained from pulse oximetry. Three respiratory-induced variations

(frequency, intensity, and amplitude) are extracted from the PPG using the Incremental-Merge

Segmentation algorithm. Frequency content of each respiratory-induced variation is analyzed using fast

Fourier transforms. The proposed Smart Fusion method then combines the results of the three respiratory-

induced variations using a transparent mean calculation. It automatically eliminates estimations

considered to be unreliable because of detected presence of artifacts in the PPG or disagreement between

the different individual respiratory rate estimations. The algorithm has been tested on data obtained from

29 children and 13 adults. Results show that it is important to combine the three respiratory-induced

variations for robust estimation of respiratory rate. The Smart Fusion showed trends of improved

estimation (mean root mean square error 3.0 breaths/min) compared to the individual estimation methods

(5.8, 6.2, and 3.9 breaths/min). The Smart Fusion algorithm is being implemented in a mobile phone

pulse oximeter device to facilitate the diagnosis of severe childhood pneumonia in remote areas.

ETPL

BME-091 Non-Contact ECG Sensing Employing Gradiometer Electrodes

Abstract: Noncontact, capacitive electrocardiogram (ECG) measurements are complicated by motion

artifacts from the relative movement between the ECG electrodes and the subject. To compensate for such

motion we propose to employ first and second order gradiometer electrode designs. A MATLAB-based

simulation tool to enable assessment of different electrode configurations and placements on human

subjects has been developed to guide the refinement of electrode designs. Experimental measurements of

the sensitivity, motion artifact cancellation, and common mode rejection for various prototype designs

were conducted with human subjects. Second order gradiometer electrode designs appear to give the best

performance as measured by signal to noise plus distortion ratio. Finally, both gradiometer designs were

compared with standard ECG recording methods and showed less than 1% beat detection mismatch

employing an open source beat detection algorithm.

ETPL

BME-092 Surgical Robot System for Single-Port Surgery With Novel Joint Mechanism

Abstract: Single-port surgery is a new surgical method performed by inserting several surgical tools and a

laparoscope through an umbilical incision. Compared with conventional laparoscopic surgery, the smaller

incision in this procedure produces a lower amount of trauma, which leads to shorter hospitalization.

However, with the current laparoscopic tools and surgical robots, the surgeon must overcome several

difficulties, such as a limited range of motion and collisions between the surgical instruments and the

laparoscope. This paper proposes a new surgical robot system for single-port surgery that uses a novel



http://www.elysiumtechnologies.com, [email protected] joint mechanism. The proposed joint mechanism is suitable for surgical instruments with multiple degrees

of freedom (DOF). Thus, it can prevent hysteresis of the joint and achieve more accurate motion with a

large force. A 6-DOF surgical instrument with this joint mechanism can avoid collisions between surgical

tools or arms and approach the surgical target more easily than a conventional straight surgical tool. The

external arm with 2-DOF passive joints can extend the workspace of the system during surgery.

Preliminary tests and validations were performed with a prototype of the system.

ETPL

BME-093

Center of Mass Acceleration Feedback Control of Standing Balance by Functional

Neuromuscular Stimulation Against External Postural Perturbations

Abstract: This study investigated the use of center of mass (COM) acceleration feedback for improving

performance of a functional neuromuscular stimulation control system to restore standing function to a

subject with complete, thoracic-level spinal cord injury. The approach for linearly relating changes in

muscle stimulation to changes in COM acceleration was verified experimentally and subsequently

produced data to create an input-output map driven by sensor feedback. The feedback gains were

systematically tuned to reduce upper extremity (UE) loads applied to an instrumented support device

while resisting external postural disturbances. Total body COM acceleration was accurately estimated

(>;89% variance explained) using 3-D outputs of two accelerometers mounted on the pelvis and torso.

Compared to constant muscle stimulation employed clinically, feedback control of stimulation reduced

UE loading by 33%. COM acceleration feedback is advantageous in constructing a standing

neuroprosthesis since it provides the basis for a comprehensive control synergy about a global, dynamic

variable and requires minimal instrumentation. Future work should include tuning and testing the

feedback control system during functional reaching activity that is more indicative of activities of daily

living.

ETPL

BME-094 An Interactive Approach to Multiobjective Clustering of Gene Expression Patterns

Abstract: Some recent studies have posed the problem of data clustering as a multiobjective optimization

problem, where several cluster validity indices are simultaneously optimized to obtain tradeoff clustering

solutions. A number of cluster validity index measures are available in the literature. However, none of

the measures can perform equally well in all kinds of datasets. Depending on the dataset properties and its

inherent clustering structure, different cluster validity measures perform differently. Therefore, it is

important to find the best set of validity indices that should be optimized simultaneously to obtain good

clustering results. In this paper, a novel interactive genetic algorithm-based multiobjective approach is

proposed that simultaneously finds the clustering solution as well as evolves the set of validity measures

that are to be optimized simultaneously. The proposed method interactively takes the input from the

human decision maker (DM) during execution and adaptively learns from that input to obtain the final set

of validity measures along with the final clustering result. The algorithm is applied for clustering real-life

benchmark gene expression datasets and its performance is compared with that of several other existing

clustering algorithms to demonstrate its effectiveness. The results indicate that the proposed method



http://www.elysiumtechnologies.com, [email protected] outperforms the other existing algorithms for all the datasets considered here.

ETPL

BME-095

Gene-Expression-Based Cancer Subtypes Prediction Through Feature Selection and

Transductive SVM

Abstract: With the advancement of microarray technology, gene expression profiling has shown great

potential in outcome prediction for different types of cancers. Microarray cancer data, organized as

samples versus genes fashion, are being exploited for the classification of tissue samples into benign and

malignant or their subtypes. They are also useful for identifying potential gene markers for each cancer

subtype, which helps in successful diagnosis of particular cancer type. Nevertheless, small sample size

remains a bottleneck to design suitable classifiers. Traditional supervised classifiers can only work with

labeled data. On the other hand, a large number of microarray data that do not have adequate follow-up

information are disregarded. A novel approach to combine feature (gene) selection and transductive

support vector machine (TSVM) is proposed. We demonstrated that 1) potential gene markers could be

identified and 2) TSVMs improved prediction accuracy as compared to the standard inductive SVMs

(ISVMs). A forward greedy search algorithm based on consistency and a statistic called signal-to-noise

ratio were employed to obtain the potential gene markers. The selected genes of the microarray data were

then exploited to design the TSVM. Experimental results confirm the effectiveness of the proposed

technique compared to the ISVM and low-density separation method in the area of semisupervised cancer

classification as well as gene-marker identification.

ETPL

BME-096

Bilinear Modeling of EMG Signals to Extract User-Independent Features for Multiuser

Myoelectric Interface

Abstract: In this study, we propose a multiuser myoelectric interface that can easily adapt to novel users.

When a user performs different motions (e.g., grasping and pinching), different electromyography (EMG)

signals are measured. When different users perform the same motion (e.g., grasping), different EMG

signals are also measured. Therefore, designing a myoelectric interface that can be used by multiple users

to perform multiple motions is difficult. To cope with this problem, we propose for EMG signals a

bilinear model that is composed of two linear factors: 1) user dependent and 2) motion dependent. By

decomposing the EMG signals into these two factors, the extracted motion-dependent factors can be used

as user-independent features. We can construct a motion classifier on the extracted feature space to

develop the multiuser interface. For novel users, the proposed adaptation method estimates the user-

dependent factor through only a few interactions. The bilinear EMG model with the estimated user-

dependent factor can extract the user-independent features from the novel user data. We applied our

proposed method to a recognition task of five hand gestures for robotic hand control using four-channel

EMG signals measured from subject forearms. Our method resulted in 73% accuracy, which was

statistically significantly different from the accuracy of standard nonmultiuser interfaces, as the result of a

two-sample t -test at a significance level of 1%.

ETPL

BME-097

Fetal ECG Extraction by Extended State Kalman Filtering Based on Single-Channel

Recordings




Abstract: In this paper, we present an extended nonlinear Bayesian filtering framework for extracting

electrocardiograms (ECGs) from a single channel as encountered in the fetal ECG extraction from

abdominal sensor. The recorded signals are modeled as the summation of several ECGs. Each of them is

described by a nonlinear dynamic model, previously presented for the generation of a highly realistic

synthetic ECG. Consequently, each ECG has a corresponding term in this model and can thus be

efficiently discriminated even if the waves overlap in time. The parameter sensitivity analysis for

different values of noise level, amplitude, and heart rate ratios between fetal and maternal ECGs shows its

effectiveness for a large set of values of these parameters. This framework is also validated on the

extractions of fetal ECG from actual abdominal recordings, as well as of actual twin magnetocardiograms.

ETPL

BME-098 Automatic Segmentation and Measurement of Pleural Effusions on CT

Abstract: Pleural effusion is an important biomarker for the diagnosis of many diseases. We develop an

automated method to evaluate pleural effusion on CT scans, the measurement of which is prohibitively

time consuming when performed manually. The method is based on parietal and visceral pleura

extraction, active contour models, region growing, Bezier surface fitting, and deformable surface

modeling. Twelve CT scans with three manual segmentations were used to validate the automatic

segmentation method. The method was then applied on 91 additional scans for visual assessment. The

segmentation method yielded a correlation coefficient of 0.97 and a Dice coefficient of 0.72 ± 0.13 when

compared to a professional manual segmentation. The visual assessment estimated 83% cases with

negligible or small segmentation errors, 14% with medium errors, and 3% with large errors.

ETPL

BME-099

A Novel Approach to Reducing Number of Sensing Units for Wearable Gait Analysis

Systems

Abstract: Gait analysis methods to estimate spatiotemporal measures, based on two, three or four

gyroscopes attached on lower limbs have been discussed in the literature. The most common approach to

reduce the number of sensing units is to simplify the underlying biomechanical gait model. In this study,

we propose a novel method based on prediction of movements of thighs from movements of shanks.

Datasets from three previous studies were used. Data from the first study (ten healthy subjects and ten

with Parkinson's disease) were used to develop and calibrate a system with only two gyroscopes attached

on shanks. Data from two other studies (36 subjects with hip replacement, seven subjects with

coxarthrosis, and eight control subjects) were used for comparison with the other methods and for

assessment of error compared to a motion capture system. Results show that the error of estimation of

stride length compared to motion capture with the system with four gyroscopes and our new method

based on two gyroscopes was close ( -0.8 ±6.6 versus 3.8 ±6.6 cm). An alternative with three sensing

units did not show better results (error: -0.2 ±8.4 cm). Finally, a fourth that also used two units but with a

simpler gait model had the highest bias compared to the reference (error: -25.6 ±7.6 cm). We concluded

that it is feasible to estimate movements of thighs from movements of shanks to reduce number of needed

sensing units from 4 to 2 in context of ambulatory gait analysis.




ETPL

BME-100

Enabling Large-Scale Ground-Truth Acquisition and System Evaluation in Wireless

Health

Abstract: Large-scale activity monitoring is a core component of systems aiming to improve our ability to

manage fitness, deliver care, and diagnose conditions. While much research has been devoted to the

accurate classification of motion, the challenges arising from scaling to large communities have received

little attention. This paper introduces the problem of scaling, and addresses two of the most important

issues: enabling robust large-scale ground-truth acquisition and building a common database for systems

comparison. This paper presents a voice powered mobile acquisition system with efficient annotation

tools and an extendable online searchable activity database with 331 datasets totaling over 700 h with 8

sensing modalities and 15 activities.

ETPL

BME-101 Prostate Brachytherapy Training With Simulated Ultrasound and Fluoroscopy Images

Abstract: In this paper, a novel computer-based virtual training system for prostate brachytherapy is

presented. This system incorporates, in a novel way, prior methodologies of ultrasound image synthesis

and haptic transrectal ultrasound (TRUS) transducer interaction in a complete simulator that allows a

trainee to maneuver the needle and the TRUS, to see the resulting patient-specific images and feel the

interaction forces. The simulated TRUS images reflect the volumetric tissue deformation and comprise

validated appearance models for the needle and implanted seeds. Rendered haptic forces use validated

models for needle shaft flexure and friction, tip cutting, and deflection due to bevel. This paper also

presents additional new features that make the simulator complete, in the sense that all aspects of the

brachytherapy procedure as practiced at many cancer centers are simulated, including simulations of seed

unloading, fluoroscopy imaging, and transversal/sagittal TRUS plane switching. For real-time rendering,

methods for fast TRUS-needle-seed image formation are presented. In addition, the simulator computes

real-time dosimetry, allowing a trainee to immediately see the consequence of planning changes. The

simulation is also patient specific, as it allows the user to import the treatment plan for a patient together

with the imaging data in order for a physician to practice an upcoming procedure or for a medical resident

to train using typical implant scenarios or rarely encountered cases.

ETPL

BME-102

Ultrasound Probe and Needle-Guide Calibration for Robotic Ultrasound Scanning and

Needle Targeting

Abstract: Image-to-robot registration is a typical step for robotic image-guided interventions. If the

imaging device uses a portable imaging probe that is held by a robot, this registration is constant and has

been commonly named probe calibration. The same applies to probes tracked by a position measurement

device. We report a calibration method for 2-D ultrasound probes using robotic manipulation and a planar

calibration rig. Moreover, a needle guide that is attached to the probe is also calibrated for ultrasound-

guided needle targeting. The method is applied to a transrectal ultrasound (TRUS) probe for robot-

assisted prostate biopsy. Validation experiments include TRUS-guided needle targeting accuracy tests.

This paper outlines the entire process from the calibration to image-guided targeting. Freehand TRUS-



http://www.elysiumtechnologies.com, [email protected] guided prostate biopsy is the primary method of diagnosing prostate cancer, with over 1.2 million

procedures performed annually in the U.S. alone. However, freehand biopsy is a highly challenging

procedure with subjective quality control. As such, biopsy devices are emerging to assist the physician.

Here, we present a method that uses robotic TRUS manipulation. A 2-D TRUS probe is supported by a 4-

degree-of-freedom robot. The robot performs ultrasound scanning, enabling 3-D reconstructions. Based

on the images, the robot orients a needle guide on target for biopsy. The biopsy is acquired manually

through the guide. In vitro tests showed that the 3-D images were geometrically accurate, and an image-

based needle targeting accuracy was 1.55 mm. These validate the probe calibration presented and the

overall robotic system for needle targeting. Targeting accuracy is sufficient for targeting small, clinically

significant prostatic cancer lesions, but actual in vivo targeting will include additional error components

that will have to be determined.

ETPL

BME-103

Magnetic Fluid Hyperthermia Modeling Based on Phantom Measurements and

Realistic Breast Model

Abstract: Magnetic fluid hyperthermia (MFH) is a minimally invasive procedure that destroys cancer

cells. It is based on a superparamagnetic heat phenomenon and consists in feeding a ferrofluid into a

tumor, and then applying an external electromagnetic field, which leads to apoptosis. The strength of the

magnetic field, optimal dose of the ferrofluid, the volume of the tumor and the safety standards have to be

taken into consideration when MFH treatment is planned. In this study, we have presented the novel

complementary investigation based both on the experiments and numerical methodology connected with

female breast cancer. We have conducted experiments on simplified female breast phantoms with

numerical analysis and then we transferred the results on an anatomically-like breast model.

ETPL

BME-104

An Extended Dynamometer Setup to Improve the Accuracy of Knee Joint Moment

Assessment

Abstract: This paper analyzes an extended dynamometry setup that aims at obtaining accurate knee joint

moments. The main problem of the standard setup is the misalignment of the joint and the dynamometer

axes of rotation due to nonrigid fixation, and the determination of the joint axis of rotation by palpation.

The proposed approach 1) combines 6-D registration of the contact forces with 3-D motion capturing

(which is a contribution to the design of the setup); 2) includes a functional axis of rotation in the model

to describe the knee joint (which is a contribution to the modeling); and 3) calculates joint moments by a

model-based 3-D inverse dynamic analysis. Through a sensitivity analysis, the influence of the accuracy

of all model parameters is evaluated. Dynamics resulting from the extended setup are quantified, and are

compared to those provided by the dynamometer. Maximal differences between the 3-D joint moment

resulting from the inverse dynamics and measured by the dynamometer were 16.4 N $cdot$m (16.9%)

isokinetically and 18.3 N $cdot$m (21.6%) isometrically. The calculated moment is most sensitive to the

orientation and location of the axis of rotation. In conclusion, more accurate experimental joint moments

are obtained using a model-based 3-D inverse dynamic approach that includes a good estimate of the pose

of the joint axis.




ETPL

BME-105

Automatic Monocular System for Human Fall Detection Based on Variations in

Silhouette Area

Abstract: Population of old generation is growing in most countries. Many of these seniors are living

alone at home. Falling is among the most dangerous events that often happen and may need immediate

medical care. Automatic fall detection systems could help old people and patients to live independently.

Vision-based systems have advantage over wearable devices. These visual systems extract some features

from video sequences and classify fall and normal activities. These features usually depend on camera's

view direction. Using several cameras to solve this problem increases the complexity of the final system.

In this paper, we propose to use variations in silhouette area that are obtained from only one camera. We

use a simple background separation method to find the silhouette. We show that the proposed feature is

view invariant. Extracted feature is fed into a support vector machine for classification. Simulation of the

proposed method using a publicly available dataset shows promising results.

ETPL

BME-106

Evoked Electromyography-Based Closed-Loop Torque Control in Functional

Electrical Stimulation

Abstract: This paper proposed a closed-loop torque control strategy of functional electrical stimulation

(FES) with the aim of obtaining an accurate, safe, and robust FES system. Generally, FES control systems

are faced with the challenge of how to deal with time-variant muscle dynamics due to physiological and

biochemical factors (such as fatigue). The degraded muscle force needs to be compensated in order to

ensure the accuracy of the motion restored by FES. Another challenge concerns the fact that implantable

sensors are unavailable to feedback torque information for FES in humans. As FES-evoked

electromyography (EMG) represents the activity of stimulated muscles, and also enables joint torque

prediction as presented in our previous studies, here we propose an EMG-feedback predictive controller

of FES to control joint torque adaptively. EMG feedback contributes to taking the activated muscle state

in the FES torque control system into account. The nature of the predictive controller facilitates prediction

of the muscle mechanical response and the system can therefore control joint torque from EMG feedback

and also respond to time-variant muscle state changes. The control performance, fatigue compensation

and aggressive control suppression capabilities of the proposed controller were evaluated and discussed

through experimental and simulation studies.

ETPL

BME-107

Controlling a Human–Computer Interface System With a Novel Classification Method

that Uses Electrooculography Signals

Abstract: Electrooculography (EOG) signals can be used to control human–computer interface (HCI)

systems, if properly classified. The ability to measure and process these signals may help HCI users to

overcome many of the physical limitations and inconveniences in daily life. However, there are currently

no effective multidirectional classification methods for monitoring eye movements. Here, we describe a

classification method used in a wireless EOG-based HCI device for detecting eye movements in eight

directions. This device includes wireless EOG signal acquisition components, wet electrodes and an EOG

signal classification algorithm. The EOG classification algorithm is based on extracting features from the



http://www.elysiumtechnologies.com, [email protected] electrical signals corresponding to eight directions of eye movement (up, down, left, right, up-left, down-

left, up-right, and down-right) and blinking. The recognition and processing of these eight different

features were achieved in real-life conditions, demonstrating that this device can reliably measure the

features of EOG signals. This system and its classification procedure provide an effective method for

identifying eye movements. Additionally, it may be applied to study eye functions in real-life conditions

in the near future.

ETPL

BME-108 Prostate Segmentation in MR Images Using Discriminant Boundary Features

Abstract: Segmentation of the prostate in magnetic resonance image has become more in need for its

assistance to diagnosis and surgical planning of prostate carcinoma. Due to the natural variability of

anatomical structures, statistical shape model has been widely applied in medical image segmentation.

Robust and distinctive local features are critical for statistical shape model to achieve accurate

segmentation results. The scale invariant feature transformation (SIFT) has been employed to capture the

information of the local patch surrounding the boundary. However, when SIFT feature being used for

segmentation, the scale and variance are not specified with the location of the point of interest. To deal

with it, the discriminant analysis in machine learning is introduced to measure the distinctiveness of the

learned SIFT features for each landmark directly and to make the scale and variance adaptive to the

locations. As the gray values and gradients vary significantly over the boundary of the prostate, separate

appearance descriptors are built for each landmark and then optimized. After that, a two stage coarse-to-

fine segmentation approach is carried out by incorporating the local shape variations. Finally, the

experiments on prostate segmentation from MR image are conducted to verify the efficiency of the

proposed algorithms.

ETPL

BME-109

Moveable Wire Electrode Microchamber for Nanosecond Pulsed Electric-Field

Delivery

Abstract: In this paper, an electromagnetic characterization of a moveable wire electrode microchamber

for nanosecond pulse delivery is proposed. The characterization of the exposure system was carried out

through experimental measurements and numerical simulations. The frequency and time domain analyses

demonstrate the utility of the proposed assembly for delivering pulses as short as 2.5 ns. High-voltage

measurements (~1.2 kV) were also performed using pulse generators based on two different technologies

with applied pulse durations of 5.0 and 2.5 ns. Validation of the delivery system was accomplished with

biological experiments involving cell electroporation with 2.5 and 5.0 ns, 10-MV/m pulsed electric fields.

A dose-dependent area increase (osmotic swelling) of the Jurkat cells was observed with pulses as short

as 2.5 ns.

ETPL

BME-110

Quantifying the Interfibrillar Spacing and Fibrillar Orientation of the Aortic

Extracellular Matrix Using Histology Image Processing: Toward Multiscale Modeling

Abstract: An essential part of understanding tissue microstructural mechanics is to establish quantitative

measures of the morphological changes. Given the complex, highly localized, and interactive architecture



http://www.elysiumtechnologies.com, [email protected] of the extracellular matrix, developing techniques to reproducibly quantify the induced microstructural

changes has been found to be challenging. In this paper, a new method for quantifying the changes in the

fibrillar organization is developed using histology images. A combinatorial frequency–spatial image

processing approach was developed based on the Fourier and Hough transformations of histology images

to measure interfibrillar spacing and fibrillar orientation, respectively. The method was separately applied

to the inner and outer wall thickness of native- and elastin-isolated aortic tissues under different loading

states. Results from both methods were interpreted in a complementary manner to obtain a more complete

understanding of morphological changes due to tissue deformations at the microscale. The observations

were consistent in quantifying the observed morphological changes during tissue deformations and in

explaining such changes in terms of tissue-scale phenomena. The findings of this study could pave the

way for more rigorous modeling of structure–property relationships in soft tissues, with implications

extendable to cardiovascular constitutive modeling and tissue engineering.

ETPL

BME-111

Massively Parallel Energy Space Exploration for Uncluttered Visualization of Vascular

Structures

Abstract: Images captured using computed tomography and magnetic resonance angiography are used in

the examination of the abdominal aorta and its branches. The examination of all clinically relevant

branches simultaneously in a single 2-D image without any misleading overlaps facilitates the diagnosis

of vascular abnormalities. This problem is called uncluttered single-image visualization (USIV). We can

solve the USIV problem by assigning energy-based scores to visualization candidates and then finding the

candidate that optimizes the score; this approach is similar to the manner in which the protein side-chain

placement problem has been solved. To obtain near-optimum images, we need to explore the energy

space extensively, which is often time consuming. This paper describes a method for exploring the energy

space in a massively parallel fashion using graphics processing units. According to our experiments, in

which we used 30 images obtained from five patients, the proposed method can reduce the total

visualization time substantially. We believe that the proposed method can make a significant contribution

to the effective visualization of abdominal vascular structures and precise diagnosis of related

abnormalities.

ETPL

BME-112

Spatial Variability of the 12-Lead Surface ECG as a Tool for Noninvasive Prediction of

Catheter Ablation Outcome in Persistent Atrial Fibrillation

Abstract: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia encountered in clinical

practice. Radiofrequency catheter ablation (CA) is increasingly employed to treat this disease, yet the

selection of persistent AF patients who will benefit from this treatment remains a challenging task.

Several parameters of the surface electrocardiogram (ECG) have been analyzed in previous works to

predict AF termination by CA, such as fibrillatory wave (f-wave) amplitude. However, they are usually

manually computed and only a subset of electrodes is inspected. In this study, a novel perspective of the

role of f-wave amplitude as a potential noninvasive predictor of CA outcome is adopted by exploring

ECG interlead spatial variability. An automatic procedure for atrial amplitude computation based on cubic

Hermite interpolation is first proposed. To describe the global f-wave peak-to-peak amplitude



http://www.elysiumtechnologies.com, [email protected] distribution, signal contributions from multiple leads are then combined by condensing the most

representative features of the atrial signal in a reduced-rank approximation based on principal component

analysis (PCA). We show that exploiting ECG spatial diversity by means of this PCA-based multilead

approach does not only increase the robustness to electrode selection, but also substantially improves the

predictive power of the amplitude parameter.

ETPL

BME-113 Reduction of the Linear Reflex Gain Explained From the M1–M2 Refractory Period

Abstract: Linear system identification methods combined with neuromechanical modeling enable the

quantification of reflex gains from recorded joint angular perturbation, torque, and/or electromyography

(EMG). However, the stretch reflex response as recorded by EMG consists of multiple consecutive

activation volleys (M1 and M2 responses) separated by a period of reduced activity and is nonlinearly

related to joint perturbation. The goal of this study is to assess to what extent linear assumptions hold

when quantifying these reflexive responses. Series of ramp-and-hold angular perturbations with fixed

velocity but different ramp durations (and, therefore, different amplitudes) were applied to the wrist joint

of seven healthy volunteers. Evoked EMG responses were compared to the reflex response estimated

from a common linear reflex model relating EMG to perturbation velocity. Model fits described the

measured EMG responses best when the perturbation and M1 response durations were equivalent. With

increasing perturbation duration, i.e., amplitude, EMG response increased but reflex gain decreased due to

the inert period after M1, which is believed to be related to alignment of the refractory period of the

motoneurons. For angular joint perturbations exceeding the M1 duration (coinciding with 2° of wrist joint

rotation in this study), reflex gain variation may be largely explained from a shortcoming of the linear

model in describing the nonlinear reflex response, and in particular the period of low reflexive activity

after M1.

ETPL

BME-114

Spectral Analysis for Nonstationary and Nonlinear Systems: A Discrete-Time-Model-

Based Approach

Abstract: A new frequency-domain analysis framework for nonlinear time-varying systems is introduced

based on parametric time-varying nonlinear autoregressive with exogenous input models. It is shown how

the time-varying effects can be mapped to the generalized frequency response functions (FRFs) to track

nonlinear features in frequency, such as intermodulation and energy transfer effects. A new mapping to

the nonlinear output FRF is also introduced. A simulated example and the application to intracranial

electroencephalogram data are used to illustrate the theoretical results.

ETPL

BME-115

A Handheld Electromagnetically Actuated Fiber Optic Raster Scanner for Reflectance

Confocal Imaging of Biological Tissues

Abstract: We present a hand-held device aimed for reflectance-mode confocal imaging of biological

tissues. The device consists of a light carrying optical fiber and a miniaturized raster scanner located at

the distal end of the fiber. It is fabricated by mounting a polarization maintaining optical fiber on a

cantilever beam that is attached to another beam such that their bending axes are perpendicular to each




other. Fiber scanner is driven by electromagnetic forces and enables large fiber deflections with low

driving currents. Optical resolutions of the system are 1.55 and 8.45 μm in the lateral and axial directions,

respectively. Functionality of the system is demonstrated by obtaining confocal images of a fly wing and

a human colon tissue sample.

ETPL

BME-116

"A Kinematic Human-Walking Model for the Normal-Gait-Speed Estimation Using

Tri-Axial Acceleration Signals at Waist Location

Abstract: This study aims at estimating the human walking speed using wearable accelerometers by

proposing a novel virtual inverted pendulum model. This model not only keeps the important

characteristics of both the biped rolling-foot and the inverted pendulum model, but also makes the speed

estimation feasible using human body acceleration. Rather than using statistical methods, the proposed

kinematic walking model enables calibration of the parameters during walking using only one tri-axial

accelerometer on the waist that collects the user's body acceleration. In addition, this model also includes

the effect of rotation of the waist within a walking cycle, which improves the estimation accuracy.

Experimental results for a group of humans show a 0.58% absolute error mean and 0.72% error deviation,

which is far better than the results of other known studies with accelerometers mounted on the upper

body.

ETPL

BME-117

Topology and Random-Walk Network Representation of Cardiac Dynamics for

Localization of Myocardial Infarction

Abstract: While detection of acute cardiac disorders such as myocardial infarction (MI) from

electrocardiogram (ECG) and vectorcardiogram (VCG) has been widely reported, identification of MI

locations from these signals, pivotal for timely therapeutic and prognostic interventions, remains a

standing issue. We present an approach for MI localization based on representing complex spatiotemporal

patterns of cardiac dynamics as a random-walk network reconstructed from the evolution of VCG signals

across a 3-D state space. Extensive tests with signals from the PTB database of the PhysioNet databank

suggest that locations of MI can be determined accurately (sensitivity of ∼88% and specificity of ∼92%)

from tracking certain consistently estimated invariants of this random-walk representation.




Education

Final Year IEEE Project 2013-2014 - Bio Medical Engineering Project Title and Abstract