The Application of Biosensors in Healthcare

IBST Launch EventUWE16/3/08

Leonard Fass Ph.D.

GE Healthcare

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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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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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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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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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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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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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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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• 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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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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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