Aimd same v09

Theory of operationArchitecture

Design

Active Implantable Medical Device Design :

The cochlear implant example

Nicolas Veau1

1Neurelec, MXM group

SAME conference, October 6th, 2010

SAME2010 Active Implantable Medical Devices


Design

Outline

1 How can an AIMD restore lost human sensory functions ?OverviewSensory processing : The auditory system exampleSensory prosthesis : The cochlear implant example

2 How can microelectronics benet to AIMD's performances ?The AIMD systemThe AIMD interfacesThe AIMD components

3 How to solve strongly coupled constraints in an AIMD design ?Modeling toolsSimulation tool



Design

OverviewThe auditory systemThe cochlear implant system

Outline






Design


What is an Active Implantable Medical Device ?Denition and examples

Medical Device: Maintain human physiological functions.

Implantable: Inserted into the human body by surgery.

Active: Uses energy to power its sensors and actuators.

Brain stimulators Heart stimulators



Design


Economical environment

1 The AIMD is mainly used for :

Sensory and functional prosthesis for invalidating disabilities.Automated drug delivery for chronicle diseases therapies.Health monitoring and prevention.Health care outsourcing.

2 The AIMD aims to :

Improve the quality of life by reducing disabilities, anxiety.Extend the life time by monitoring vital signs.Decrease the societal cost by improving the patient autonomy.

3 The AIMD market growth is driven by :

The rehabilitation of disability considered as a public priority.The population aging.The over weighted people growth.The emergence of new geographic markets.



Design











Design











Design


Outline






Design


The auditory systemHow does the ear work ?

External Ear: Antenna & amplier & conduction line

Middle Ear: Impedance matching & Automatic Gain Control

Inner Ear: Analog-to-Digital Converter



Design


The auditory systemHow does the internal ear work ?

Basilar membrane: Transform pressure variation in membranedisplacement. Behave as an analog delay line.

Corti Organ: Sense the displacement pattern on the basilarmembrane.

[2]



Design


The auditory systemHow does the inner ear work ?

Inner Hair Cell: Amplitude time-space sampler. Low frequencydetector.

Outer Hair Cell: Frequency and phase time-space sampler. Up to16kHz detector.

[2] [3]



Design


The auditory systemAuditory pathway from the inner ear to the brain

Auditory pathways: Autocorrelators & feedback loops

Cortex: Correlators and associative memory

[2]



Design


Outline






Design


Cochlear ImplantHow does the cochlear implant work ?

External ear & middle ear <=> Microphone & DSP

Inner hair cell & Outer hair cells <=> Electrode array

[1]



Design


Cochlear ImplantClinical needs and their impacts on the electronics requirements

1 Reliability

1 System reliability2 Data transfer reliability

2 Clinical performance

1 Good signal processing for voice, music, noise environment2 Better stimulation with higher temporal and spatial resolution3 User friendly interface4 Data fusion

3 Low invasiveness

1 Miniaturization2 Maintenance surgery3 Active time



Design

The AIMD systemThe AIMD interfacesThe AIMD components

Outline






Design


AIMD architecturePhysical view

Subsystems :

StimulationSensorsEnergy transfer/storageCommunications

Constraints :

ConnectionsEncapsulationManufacturingAgreements



Design


AIMD architectureFunctional view



Design


AIMD architectureData path view



Design


Outline






Design


Electrode arrayCharacteristics

Clinical targets :

Preserve neuronsActivate neurons on demandMonitor neuron activity

Electrode array characteristics :

Mechanical control : toxicity, insertion trauma, infectionPrecise current control : in amplitude, time, in spaceTissue impedance measurements

Electrode arrays

[4]



Design


Electrode array3D current control

Virtual electrodes : Allow current steering and focusing for higherneuron selectivity.

Complex waveforms : Allow better neuron preservation andecient stimulations.

Virtual electrodes concept

[4]



Design


Implantable sensorsThe interface with the outside world

Acoustic sensor

Low noise, low power

Automatic gain control.

Helium-leak test compliant

Low prole, small volume

Bio-signal sensorRAIC

t pic N1 : entre 200 µs et 300 µs

pic P1 : 700 µs

entre 400 µs et 500 µs

fRAIC comprise entre 1 kHz et 1,5 kHz

Amplitude des RAIC comprise entre 20 µV et 1 à 2mV selon le courant de stimulation utilisé.

Neural response

Neural synchrony

Stimulation loop back

Time variability oset



Design


Radio communicationTrans-cutaneous communication interface

Usages: Remote control, tting, multimedia accessories

Figures: Below 3mW in 64kbps DL. Below 1µW in standby.1Mbps max.

Dilemma: Energy/Data transfer, Magnetic/Electromagnetic

Link budget

Description du canal de propagation:

Peau Cartilage Graisse Equivalent

Epaisseur 1 mm 4 mm 34 mm 39 mm Permittivité relative r

38.01 38.77 5.28 9.55

Conductivité

44.25 52.63 8.55 13.98

Facteur de perte

0.0226 0.0190 0.1170 0.07151

http://niremf.ifac.cnr.it/tissprop/htmlclie

Caractéristiques des 3 tissues du model équivalent à 2.45 GHz

Loss between external ear andimplant : - 25dB @ 2.45GHz

Antenna

Antenne IFA ( Inverted Antenna)Définition:

Antenne IFA dessinée sous HFSS

Modèle réalisé sous HFSS

L 30.35 mm l 0.5 mm H 2 mm S 1 mm

F=2.45GHz, BW=80MHz,Zin=50Ω



Design


Outline






Design


Battery

Safety : Backup system, safe chemistry, hot swap,EN45502-2-3.Protection : Titanium casing with feed-through, over andunder charge, emergency stop.Energy transfer : Capacity vs., charging time, charging timeafter 10 years.Inductive charging : EN45502-2-3, expected eciency above70%Energy distribution : 0.9 V.



Design


Processing units

1 Intensive processing routines : Physiological noise ltering,artifact reduction, sensor data fusion, stimulations building,signal features extractions ...

2 Processing units : ASIC, ASP, FPGA, DSP, DMA, MCU3 Software architecture : Usually no RTOS, no vendors libraries

for safety reasons, specic development and test guidelines.

Generic datapath



Design

Modeling toolsSimulation tool

Outline






Design


Analytical modelsMulti-physics models

1 Captures tight physics interactions : acoustic, viscosity andthermal combined eects.

2 Ecient for variable sensitivity analysis and optimization underconstraints.

3 Supported by simpler and easier to understand lumpedelements representations.

Subcutaneous microphone

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Ossicular chain model

2. Comparisons of model and data ensembles

Figure 4 shows mean and mean±standard error of themean !SEM" curves of the Vst / P!tm measurements !circularmarkers" and curves of the model with the TM !up-pointingtriangular markers" for set A #Fig. 4!a"$, and set B #Fig. 4!b"$,along with the corresponding Vst noise floor measurementsnormalized by P!tm. In #Fig. 4!c"$, the model fit to the meanof all 16 ears !AB" is shown, with and without the TM !up-pointing and down-pointing triangular markers, respec-tively", along with the mean and mean±SEM curves for the16 ears in sets A and B !circular markers". For comparison, aVst / Pec mean magnitude curve, based on measurementsmade by Huber et al. !2001" on seven living ears, is alsoshown in Figs. 4!a"–4!c" !square-shaped markers", for whichmagnitude adjustments were made by Chien et al. !2006" onfrequencies below approximately 2 kHz to account for pos-

sible methodological differences between living ear and tem-poral bone ear studies. Also for purposes of comparison,Vst / P!tm model curves from three other studies are shown inFig. 4!c": Kringlebotn, 1988 !x-shaped markers"; Goode etal., 1994 !no markers"; and Feng and Gan, 2004 !"-shapedmarkers". For set A, the mean model and measurement mag-nitudes !upper half of Fig. 4!a"" show generally good agree-ment over the full frequency range, with the exception of thepeak in the data near 12 kHz !due to the inability to matchthe peaks seen in A3 and A4: see Fig. 3". In the measure-ments for set A the signal to noise ratio for the mean mag-nitude falls below 6 dB above 11.5 kHz, however. Somesmaller differences between the means can be attributed tothe inability to fully match the peaks and dips in the0.8–2 kHz vicinity, as well as some other cases where peaksand dips in the model do not correspond to features in the

FIG. 2. !Color online" Model of the TMOC block depicted in sections B and C of Fig. 1, in its original form !A" and an alternate form in which the effectsof the three transformers have been absorbed into the model parameters !B". The tympanic membrane is represented as a one-dimensional acoustic transmis-sion line with associated delay Ttm and characteristic impedance Z0tm. The ossicular chain and cochlea are represented as a network of electrical circuitelements with acoustic or mechanical interpretations !see definitions within the figure". Section A depicts the TMOC model adapted from Puria and Allen!1998", with three transformers representing the effects of the TM area !Atm", the effective lever ratio of the malleus-incus complex !NLR", and the area of thestapes footplate !Afp". Section B shows an alternate version of the model in section A with the transformers “removed” such that all variables are representedby their acoustic equivalents as seen from the left of all three transformers. Variables redefined in this way have a “T” appended to their subscripts to indicatethat they have been “Transformed,” and equations are shown under the panel for converting between transformed and untransformed versions of the variables.In the case of impedance blocks, such as ZmT for the malleus, the same conversion equation applies for all elements within the block !i.e., MmT, KmT, and RmTin this case". By redefining the variables in this manner, it becomes possible to make direct quantitative comparisons between variables that were previouslylocated on opposite sides of one or more transformer. For this reason the transformed version of the circuit !section B" was used for much of the model-fittingprocedure. To convert the transformed parameter values to their untransformed equivalents, values of 6#10!5 m2 for Atm, 1.3 for NLR, and 3.14#10!6 m2 forAfp are used.

J. Acoust. Soc. Am., Vol. 123, No. 1, January 2008 K. N. O’Connor and S. Puria: Human middle-ear circuit model parameters 203

[5]



Design


Analytical modelsStatistical and biological models

1 The model computes the neurons population recruited byelectrical stimulation according to their ring rate.

2 This model is used to identify the virtual electrodes thatmaximize spatial selectivity and directivity of a stimulation

Current focusing and steering

Current Focusing − Contour Plot of Number of Neurons Fired

σ values

Loca

tion

(x)

0 0.2 0.4 0.6 0.8 1−2.5

−2

−1.5

−1

−0.5

0

0.5

1

1.5

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2.5

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−2.5 −2 −1.5 −1 −0.5 0 0.5 1 1.5 2 2.50

10

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90

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Location along Neural Clusters(x)

Neu

rons

Fire

d

Current Focusing − Number of Neurons Fired

σ = 0σ = 0.5σ = 0.75σ = 1electrode

Current Steering − Contour Plot of Number of Neurons Fired

α values

Loca

tion

(x)

0 0.2 0.4 0.6 0.8 1−2.5

−2

−1.5

−1

−0.5

0

0.5

1

1.5

2

2.5

0

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−2.5 −2 −1.5 −1 −0.5 0 0.5 1 1.5 2 2.50

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Location along Neural Clusters(x)

Neu

rons

Fire

d

Current Steering − Number of Neurons Fired

α = 0α = 0.25α = 0.5α = 0.75α = 1electrode



Design


Numerical modelsPhysics models

1 Useful for complex geometry and numerous interfaces

2 Reduce the number of prototypes and cost

3 Computations intensive, slow optimization convergence

4 Expensive tools, dicult to set them up, lack ofinteroperability with others tools.

Antenna Magnetic systems Piezoelectric systems



Design


Numerical modelsStatistical and biological models

A simplistic 3D model of the cochlea

Accompanying electrode array

Generated potentials and currents through the cochlea whenthe electrodes were stimulated.

Neural response to electrical stimulation was observed.

BEM and HodgkinHuxley model method

[6]



Design


Outline






Design


Cochlear implant simulator


Bibliography I

[1] Digisonic SP systemhttp://neurelec.com/

NEURELEC, Vallauris

[2] Pujol R. & al.Extracts from the website "Promenade autour de la cochlée"http://www.cochlee.org

INSERM U. 254, Montpellier

[3] Kiang N., Rho J., Northrop C., Liberman M. & Ryugo D.Hair-cell innervation by spiral ganglion cells in adult catsScience, 1982, 217, 175-177

[4] Cu electrodes.http://neurelec.com

NEUROMEDICS, Vallauris


http://neurelec.com/

http://www.cochlee.org

http://neurelec.com

Bibliography II

[5] O Connor K.N. & Puria S.Middle-ear circuit model parameters based on a population ofhuman earsThe Journal of the Acoustical Society of America, 2008, 123,197

[6] Gramfort A., Papadopoulo T., Olivi E., & Clerc M.OpenMEEG: opensource software for quasistaticbioelectromagneticsHAL-INRIA. May 2010.


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Aimd same v09