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The Application of Biosensors in Healthcare
IBST Launch EventUWE16/3/08
Leonard Fass Ph.D.
GE Healthcare
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29/11/06
Need for Patient Centric Healthcare• Aging population
– 20% 0ver 65 by 2030 in USA (12% today)– 38% of hospital in-patients
• Increase of Chronic age related diseases– 80% of all patients have chronic illness– US: Cost in 2005: $510B -> 2010: $1,07T – Exponential increase of CHF and Alzheimers with age – Most hospitals built around acute care
– Type 2 Diabetes– Cancer– Congestive Heart Failure– COPD– Arthritis– Osteoporosis– Dementia– Sleep apnea
• High level of medical and administrative errors
Rising health care costs driving community based medicine
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29/11/06
Healthcare is Changing
PatientsPhysiciansSpecialities
PhysiciansSpecialities
PhysiciansSpecialities
PhysiciansSpecialities
PhysiciansSpecialities
PhysiciansSpecialities
PhysiciansSpecialities
PhysiciansSpecialities
Patients
Patients
Patients
Patients
Patients
Patients
Remote patient monitoring and body sensor networks will be key drivers of patient centric healthcare
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Technology Innovation helping Patient Centric Healthcare
•Point of Care diagnostic tests• Nanotechnology based disposable blood tests
• Wearable & implantable body sensor networks• Pocket ultrasound systems replacing stethoscope• Wireless transmission of data• Available at home, doctor`s office & ambulance• ECG on mobile phone SIM cards• EMR Integration
•Augment Clinical Decision support algorithms•Link physicians, Payers, Hospital RPM data
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Technology Developments driving Pervasive Wireless Sensor Networks
•Advances in low power wireless communication•Miniaturization of semiconductor devices•Cost reductions of processors•Increased processing capability•Novel sensor technology •Sensors with on-board processing and wireless data transfer capability•Energy storage technologies
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29/11/06
Health Care Objectives for Wireless Sensor Networks
•Minimise error rates
•Conduct diagnoses with real time patient data
•Improve efficiency
•Reduce costs
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The Need for Body Sensor Networks
•Wireless Sensor Networks do not match the needs of the human body
– Complicated internal environment – Responds to & interacts with external stimuli– Self contained system– Specific sensors– Real time monitoring
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Characteristics of Body Sensor Networks
•Personalized monitoring system
•Context aware
•Invisible to the subject– No activity restriction– No behaviour modification
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Wireless and Body Sensor Networks
•Cover the human body•Fewer sensor nodes•Single multitasking sensors•Robust & Accurate•Miniaturization•Pervasive•Predictable environment•Motion artefacts an issue•Early adverse event detection•Failure irreversible•Variable structure
•Cover the environment •Large number of nodes •Multiple dedicated sensors•Lower accuracy•Small size not limiting factor•Resistant to weather, •Resistant to noise•Resistant to asynchrony•Early adverse event detection•Failure reversible•Fixed structure
WSN BSN
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Wireless and Body Sensor Networks
•Low level security•Accessible power supply•High power demand•Solar,wind power•Replaceable/disposable•No biocompatibility needed•Low context awareness•Wireless solutions available•Data loss less of an issue
•High security •Inaccessible power source•Lower power availability•Thermal, piezoelectric energy•Biodegradeable•Biocompatible•High context awareness•Lower power wireless•Sensitive to data loss
WSN BSN
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Autonomic Sensing similar to the Autonomous Nervous System (ANS)
•The ANS controls the body's internal environment in a coordinated manner•The ANS helps control the heart rate, blood pressure, digestion, respiration, blood pH and other bodily functions through a series of complex reflex actions•The ANS has 2 Divisions, Sympathetic and Parasympathetic, which differ in Anatomy and Function• Autonomic nerves go from spinal cord to: lungs. heart,stomach, intestines, bladder & anal sphincters, genitals•The Hypothalamus has central control of the ANS•The Adrenal Glands activate in emergencies•Body Sensor Networks using Autonomic Sensing will function in a similar manner
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Autonomic Nervous System
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Trust, Security
and Policy
Self-configuration, healing,
managing of software components
Network Storage
and Decision Support Agents
Multi-sensor Analysis
and Fusion
Environment Sensors and
Context
Autonomic Sensing
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29/11/06
Current Monitoring Tools
Special Tests
Imaging
Peak Flow
ECGO2 Sats
Blood Pressure
Blood Tests
Exam
History
Medical Records
Patient
Only a SNAPSHOT of a patient’s health
Continuous monitoring is needed for real time patient management
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Biosensor Design
Biocompatibility & Materials
Wireless Communication
Low Power Design &
Scavenging
Autonomic Sensing
Standards & Integration
BSN
BSN components
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Wireless autonomous transducers
Enabling technologies
- Ultra-low-power wireless - Ultra-low-power signal processing - Micro-power systems - Sensors and actuators - Integrated sensor platforms (2D and 3D)
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Radio frequencies of Wireless Networks for data transmission
Protocols used in personal monitoring include Bluetooth and IEEE802.11b.
Weeks R, Dumbill E, Jepson B, 2004, “Linux Unwired”, O’Reilly Media Inc.
Wireless network Frequency Range
802.15 (Bluetooth)
802.11. 802.11b. 802.11g
802.11a
802.15 (Bluetooth)802.15.4 (Zigbee)
GPS
2.45 GHz2.4GHz
2.4 to 2.483 GHz
5.180 to 5.805 GHz
1.2276 to 1.57542 GHz
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BSN Node Structure
RF moduleUltra low power processor
Tiny OS Operating System
•BSN Node captures data from a sensor•Performs low level processing •Transmits data to a Local Processing Unit
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Power Requirements for Body Sensor Nodes
Power is needed to operate the:– Sensor– Signal conditioning & data processing circuitry
– ADC is main component– Trend towards Ultra Low Power Bio-Inspired Signal
Processing– Hybrid analogue/digital processing systems
– Wireless data link
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29/11/06
Low data rates for body sensors usually mean low power
Signal Depth
bits
Rate
/min
Data Rate
Bits/minHeart Rate 8 10 80
Blood Pressure
16 2 32
Temperature 16 1 16
Blood Oxygen
16 1 16
Low clock rates on the circuit Low transmission power for the wireless uplink
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Power Sources for Wireless Sensor Nodes
•Most wireless sensor nodes are presently powered by
batteries.
•Replacement of batteries is costly
•Battery large enough to last the lifetime of the device would
dominate the overall system size and cost
•Alternative power sources are being developed
•These power sources may use a battery or capacitor as a
buffer when system is not being used
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Power Source
Power density J/cm3 μW/cm3/yr Secondary storage
Voltage regulation
Product available
Primary battery - 2880 90 No No Yes
Secondary battery - 1080 34 No Yes
Micro fuel cell - 3500 110 ? ? No
Ultra capacitor - 50-
1001.6-3.2 No Yes Yes
Heat Engine - 3346 106 Yes Yes No
Radioactive (63Ni)
0.52 μW/cm3 1640 0.52 Yes Yes No
Vibrations 200 μW/cm3 - - Yes Yes No
Human power
330 μW/cm3 - - Yes Yes No
Temperature 50 μW/cm2 - - Yes ? Almost
Solar (outside)
15000 μW/cm2 - - Yes ? Yes
Solar (inside) 10 μW/cm2 - - Yes ? Yes
Alternative Power Sources
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Biosensors•A biosensor involves a bio-recognition event that causes some sort of physico-chemical change, that is transduced into a measurable signal.•Dominant technology for biosensors is electrochemistry•Electron tunnelling at electrified interface•Amperometric devices
– Non equilibrium applied potential– Electrode surface and potential determine selectivity– Limited to analytes oxidized in the potential range of
water (-0.9V to +1.2V)
•Potentiometric devices– Active element is membrane or oxide coating– System in equilibrium– Neutral species cannot be sensed
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Electrochemical
pH
Thermometric
Optical
Magnetic
Piezoelectric
Biosensor
Signal
Physico- chemical Transducer
Change
Biomolecular recognition event
–Binding (affinity)–Chemical reaction–Release of a detectable species
Enzyme
Antibody
Micro-organism
Cell
Aptamer
Nucleic Acid
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Redox Mediators•Covalent attachment of electron-relay units at the protein periphery as well as inner sites, yields short inter-relay electron-transfer distances
•Electron ‘hopping’ or tunneling between the periphery & the active site enables electrical communication between the redox enzyme & its environment
•Simplest systems of this kind involve electron relay-functionalized enzymes diffusionally communicating with electrodes
•Complex assemblies include immobilized enzymes on electrodes as integrated assemblies
•Chemical modification of redox proteins with synthetic electron mediators is accompanied by partial denaturing of the native biocatalyst
•Modification must be carefully controlled to achieve the optimum effect
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Redox Mediators
Ferrocene unit
Os-complex+ lysine amino group
Ferrocene unit + Schiff Base
Ru-complex + pyridine
Ru(bpy)3His-complex
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Glucose-oxidizing enzymes attached with gold nanoparticles to electrodes
Potential for use as biosensors to measure blood glucose
I.Willner Jerusalem
• Nanoparticle plug on enzyme
• Redox mediator
• Enzyme such as glucoseoxidase oxidizes glucose to gluconic acid
• Example gold/ferrocene(Fe(C5 H5 )2) -actin/biotin-glucoseoxidase
• Electrons flow through nanoparticle into the electrode
• Amount of current indicates level of glucose present
• Could be used as feedback mechanism for insulin pump
• Potential for glucose fuel cells
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Diabetes Patient Management a Focus of Remote Sensing Developments
•Global Prevalence – 2.8% in 2000– 4.4% in 2030
•Persons affected– 171 million in 2006– 366 million in 2030 [Wild et al., 2004]
•1995-2025 increase: – 40% in industrialized countries – 170% in developing countries
•90% suffer from Type 2 Diabetes
Diabetes Monitoring Technologies
•Implantable skin sensors
•Photo-acoustic redox mediator watch sensor(Glucon)
•Eye refractive index (LEIN AD)
•Feedback loop insulin pump (Medtronics, Abbot)
•Interstitial Fluid (SPECTRx )
•Blood glucose
•Pain free 0.6mL (Abbot)
•Interstitial Fluid (SPECTRx )
•Implantable skin sensors
•Photo-acoustic redox mediator watch sensor(Glucon)
•Eye refractive index (LEIN AD)
• Feedback loop insulin pump (Medtronics, Abbot)
•A1C Test
•Glucose
Continuous/WirelessContinuous
Technologies
Clin
ical
Pra
ctic
e
Continuous & Single use Continuous & Single use
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Patient Compliance
•Compliance of diabetes patients between 60-80%
•Complications due to multiple medications
•Driving continuous monitoring of blood glucose
•Development of automatic insulin delivery
•Need for fail-safe delivery system
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Continuous Glucose Monitoring System
Amplifier- Transmitter:Powers the sensor & transmits the glucose readings
Receiver:
Displays the glucose readings
Directional arrow indicates increase/decrease
Provides different alarms when the actual or impending readings are high or low
Ben Feldman, Abbott Diabetes Care,
Diabetes Technology Mtg, Philadelphia, October 29, 2004
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Feedback Loop-Based Individualized Drug Administration
3 Day Patch•Calibrator•RF receiver•Drug reservoir•Pump•Battery•Miniature subcutaneous drug inlet
Implanted 3 day battery powered sensor/amplifier/ transmitter
Courtesy Prof. Adam Heller
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Nanotechnology and Biosensors
Nanotechnology will contribute to a wide range of diagnostic applications through the development of:• Implantable Diagnostic Devices• Internal Diagnostics• Intracellular Diagnostics• Pathogen Detection
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In-vivo Sensor–Organic sensor–With telemetry–100 microns–Biocompatible–Biodegradable
Bio-Sensors & Actuators
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Biosensor Design
Thermistor
ECG
SpO2
Glucose concentration
Blood pressure
pH measurement
Capsule endoscopy
Implant blood pressureflow sensor (CardioMEMS)
Glucose sensor(Glucowatch)
Thermistor(ACR system)
Implant ECG recorder(Medtronics –Reveal)
Oximeter(Advanced Micronics)
Implant pH sensor(Metronics – Bravo)
Pill-sized camera(Given Imaging)
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Biocompatibility and MaterialsBiosensors
Stents
Tissue Engineering
• Pattern & manipulate cells in micro-array format
Drug delivery systems
Carol Ezzell Webb, “Chip Shots”IEEE Spectrum Oct 2004
Smart Pill – Sun-Sentinel Co.
Implant blood pressureflow sensor (CardioMEMS)
Drug releasing stents - Taxus stents - Boston Scientific Co.
Ozkan et. al (2003), Langmuir
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New Applications of Biosensors•Stent Monitor
• Restenosis• Pressure gradients• Plaque build-up• Artery thickening
•Smart Catheter• Fibrillation Detection
•Post-operative Patient Monitoring
•Drug Delivery
•Radiation Therapy• Dynamic Dose Control, • Micro-Targeting• Reconstruction Aid (angular uncertainty)
Pill Imager
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29/11/06
Solid State Ultrasound Sensors
Enabling TechnologiesIntegration
• MEMS transducer and electronics in the same miniature circuit
Miniaturization• Highest density, performance interconnect &
packaging
cMUT MEMS ArrayCapacitive micro-fabricated ultrasonic transducers
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Example of cMUT Cell
Silicon Nitride Membrane 650nm thick
Top Electrode of Aluminium
Silicon Nitride Support
Vacuum Cavity 100nm
Silicon Wafer Substrate
Electrostatic Cell
Insulating Layer 200nm
Bottom Electrode
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Ubiquitous ultrasound in primary care •Ultrasound for every physician •Tomorrow’s Stethoscope•Ultrasound patch sensors with wireless continuous monitoring
160kg 4.5kg < 1kg
0.1kg
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Stent and Catheter Developments• Biodegradeable, Drug-Eluting Stents (DES)• BioMEMS sensor stents and catheters
Stentenna – transmits blood flow and pressure dataCourtesy U. of Michigan
BioMEMS Catheter Technology
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• Molecular recognition
• Structured NanoMaterials through self-assembly
• Biocompatible IC technology
• Sensor & electronics design & packaging
Multiple Technologies for Nano BioSensors
1st SiC Analog-Digital Op-amp
(GE Global Research, 2002)
Nanowires (GE Global Research, 2002)
Organic LED (GE Global Research,
2002)
Self Assembled Thin Films (GE Global Research, 2002)
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• Enabling Technologies– Nanotubes & nanowires– Quantum dots– Hybrid
organics/inorganic
Nano BioSensors in the ER
• Benefits– Real time, in situ reading of
biochemical activity– Cellular level optical
imaging– Sensor guided precision
surgical tools
Nanowires GE Global Research (2002)
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29/11/06
Nano BioSensors in the Doctor`s Office
• Benefits– Total blood analysis in
minutes– Rapid, accurate disease
diagnosis– Patient specific disease
treatment
Self Assembled Block Copolymer Thin Films (GE Global Research, 2002)
• Enabling Technologies– Molecular recognition– High density nano-arrays
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29/11/06
• Enabling Technologies– Wireless
communications– Self powered devices– High resolution displays
Nano BioSensors at Home
Organic Light Emitting Diode (GE Global Research, 2002)
• Benefits–Simple patient administered diagnostic tests–Automatic transmission ofoutpatient data from home tothe doctor
Integrated Hall Effect Sensor (GE Global Research, 1998)
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29/11/06
Percutaneous Monitoring with Miniature Sensors•Digital plaster device checks vital signs such as:
– Temperature– Blood pressure– Glucose levels
•Results via modem or PDA to a computer
•Out of range readings give alarm
•Based on hybrid analogue/digital CMOS semiconductors
Toumaz Technology
Device 3x5mm
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29/11/06
Movement and Physiological Monitoring
Movement
•Gait patterns
•Fall characteristics
•Level of general activity
•Postural sway
•Eating & Drinking
Physiological
• Heart rate
• ECG
• Respiration rate
• Hydration
• Glucose level
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Self-Configuring Blob-Sensors - from Blob to Personal Metrics to Behaviour Profiling
IBE Imperial College
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Spherical depth map
From Blob to Personal Metrics to Behaviour Profiling Standing
SittingLying down
IBE Imperial College
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Contextual Patient Based Analysis
Parameter Based AnalysisParameter Based Analysis• Unlinked parameter acquisition and
analysis• Parameters alarm independently of
each other
Contextual Patient Based AnalysisContextual Patient Based Analysis• In-context parameter evaluation• Identify lead failure, artifact, • Improve clinical accuracy and
relevance• Reduced false alarms
Data Flow From
Patient
Data Flow From
Patient
Para
met
er A
larm
sPatientAlarm
Merging & integrating algorithms to provide “smarter systems”
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PatientHome
Central RPM Data Services
Hospital
HomeHub
RPM Data
Server
Secure Network
Secure Network
Secure, Mobile Access
Remote Patient Monitoring (RPM) System
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Applications of RPM System
•Patient Dashboards•Analysis•Alerts•Messaging•Reporting
Physicians
•Patient Metrics•Population Metrics•Predictive Modelling•Statistics / Trending
Epidemiologists
•Med Reminders•Test Reminders•Doctor E-mail / Paging•Patient Education•Positive Reinforcement
Patients
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Parameters measured remotely- Weight
- Oxygen
- Blood Pressure
- Blood Glucose
- Heart Rate
- Actigraphy
- Heart Sounds
- Breathing Sounds
- Sleep Apnea
- Hydration
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Activity Monitoring with Home Activity Sensors
•Tracking: Monitors sleep, eating & activity patterns
•Adaptive Modelling: Learns normal patient activity patterns & identifies deviations
•Diagnostic Capability: Identifies drug side effects (e.g. insomnia, fatigue, sleep disorders))
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Normal Sleep Pattern in Healthy Patient
Highly Fragmented Sleep Pattern in Dementia Patient
Weekly Patient Activity Chart
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Chronic Care Platform
EMR Integration
Predictive Modeling
Novel Applications
Next-Gen Sensors
Advanced Informatics
Behaviour Modification
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EMR IntegrationAugment Clinical Decision support algorithmsLink physicians, Payers , hospital RPM data
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Next-Generation Sensors
Minimally invasive sensors:Sleep ApneaActivity MonitoringHydrationWearable Patient Monitor
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Novel Applications
Medication remindersDrug Rx RefillsPatient Event Reminders/alerts Home Care Auditing (Fraud detection)
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Patient Risk Assessment & Education .. empowermentIx: Information prescriptionPatient education … timed with EMR events..
Behaviour Modification
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Predictive ModelingToday: Identify trends, stratify risk .. Early interventionFuture: Diagnostic algorithms
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Data fusionPopulation modelingData miningAdaptive modeling
Advanced Informatics
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Physiological Monitoring for CHF• Cardiac Rhythm
– ‘Event monitoring’ (‘Holter’ type)– Implanted Pacemaker based– Implanted ICD based
• Contractility– Left Ventricular Ejection Fraction– Ventricular Volumes (Right, Left, Diastolic, Systolic)– Shortening Fraction – Wall Diameters (Right, Left)
• ‘Flows’ and ‘Pressures’– Electrocardiogram (ECG)– Doppler Flows– Ventricular Pressures (Left, Right, End Diastolic)– Blood pressure
• Oxygen Saturation– SpO2 monitoring
• Sleep Apnea– EEG Entropy changes, Oxygen saturation decrease
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Disease Management DashboardExample Congestive Heart Failure Screen
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Sleep Apnea and Cardiovascular Disease
Sleep Apnea increases:– Risk of Cardiovascular disease 4.6 times– Apnea-associated oxygen desaturation– Hypertension– Inflammatory processes (CRP increase)– Atrial fibrillation occurrence– Higher plasma viscosity and fibrinogen in evenings
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Wireless solutiontechnically feasible for home based sleep studies
Falling asleep
For details see: Acta Anaesthesiol Scand 2004, 48(2): 154-161
Depth of Anaesthesia by ENTROPY of EEG
16
16 -
Wireless solution technically feasible for home based sleep studies
Falling asleep
-
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Sleep stage monitoring
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Summary
Future healthcare will need to manage a large increase in chronic disease with limited resources
Patient Centric Healthcare will be help to optimize disease management in the hospital and the community
Remote Patient Monitoring and Body Sensor Networks will be key elements facilitating Patient Centric Healthcare