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WEARABLE SENSOR TECHNOLOGY Bonato & Chan. Overview  Describe clinical need for wearable sensors  Discuss sensor functionality  Present technical aspects.

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Presentation on theme: "WEARABLE SENSOR TECHNOLOGY Bonato & Chan. Overview  Describe clinical need for wearable sensors  Discuss sensor functionality  Present technical aspects."— Presentation transcript:


2 Overview  Describe clinical need for wearable sensors  Discuss sensor functionality  Present technical aspects of sensor/system implementation (e-textile and wireless)  Provide specific examples of sensors/systems developed by European groups  Gloves  Shirts  Bed linen

3 Motivation  Health Care Reform (Independence at Home Medical Practice Demonstration Program)  electronic health information systems, remote monitoring, and mobile diagnostic technology  Less intrusive patient monitoring  Improve diagnoses  Enhance safety  Increase community participation  Maintain independence

4 Motivation  Community Based research  Take the gait lab out of the hospital  Measure research phenotyping  Medication titration N of 1 trials

5 EUROPEAN COMMISSION Peter Wintlev-Jensen and Andreas Lymberis

6 Percentage of GDP (EU27) Source: EC '2009 Ageing Report: economic and budgetary projections for the EU-27 Member States (2008-2060)' Motivation

7 Framework Programme 7 ICT research ICT & Aging  Advanced Prototypes for independent living/active aging (Ambient Intelligence, Robotics)  Open Systems, Reference Architectures, Platforms  Support: roadmaps, ethics, standards, Int’l cooperation Currently~30 projects, ~90 M€ funding Motivation

8 46,500 hospital bed days saved by facilitating early hospital discharge 225,000 care home bed days saved by delaying the requirement for people to enter care homes 46,000 nights of sleep-over care and 905,000 home check visits saved by substitution of remote monitoring arrangements Collectively, these savings are valued at around £43 million - an anticipated benefit to program funding cost ratio of 5:1. TELECARE IN SCOTLAND Motivation

9 Utility  Physiological Monitoring ECG Body Temp Blood pressure Respiratory Rate Oxygen saturation Surface EMG Biomarkers (sweat) Sympathetic/parasympath etic balance (e.g. mood)

10 Utility  Movement monitoring Body position (e.g. falls) Activity monitoring Energy expenditure  Geolocation Track activities Localize people in need of urgent clinical care Fuse with sensors embedded in the environment  Merging with survey data gathering in the field Merging sensor and survey data

11 Related clinical conditions  Cardiac arrhythmias - 15 million  Sleep Apnea- Millions  Sudden Infant Death Syndrome 2,000/year  Nursing home  Falls 10%/year

12 Wearable Sensor Categories  Ambulatory Systems  First generation systems based on traditional sensor technology and data loggers (similar to Holter systems) with limited capability.  Cloth-Based Systems  Second generation systems based on sensors integrated in garments and relying on either wireless technology or e-textile solutions for data gathering.

13 First Generation (Ambulatory) Systems  NASA Lifeguard (2004)

14 Second Generation (Wearable) Systems  Systems based on wireless technology or e-textile solutions to gather and relay data to a remote site.

15 Second Generation (Wearable) Systems

16 Sensor Technology  Electrical resistance  Piezoelectric  Hall Sensors  Foam based  Wires wrapped around thread  Traditional Electrodes  Wireless controls

17 Examples  Zurich  Pisa  Madrid  Twente


19 Instrumented Glove To date, the gloves developed, as far as now, present drawbacksTo date, the gloves developed, as far as now, present drawbacks - sensor saturation - sensor signal drift - not being able to record all finger joints To overcome these drawbacks, a new sensorized glove has been developed: the NeuroAssess GloveTo overcome these drawbacks, a new sensorized glove has been developed: the NeuroAssess Glove NeuroAssess Glove

20 Specifications: -6 resistive bend sensors -0.5° resolution -0.9° repeatability error -± 3° accuracy -100 Hz sampling rate Instrumented Glove

21 SMARTEX AND UNIVERSITY OF PISA Prof. DeRossi and Dr. Paradiso

22 Overview  Smartex (spin-off of University of Pisa) - Goal is to use textiles as a platform for unobtrusive monitoring  Devised a novel way of “printing” piezoelectric sensors onto elastic cloth at very low cost  10 years old-company with 10 staff  Funding Milan textile industry, DARPA, NIH  Functional focus-manipulation, posture, balance, transfers and locomotion

23 Smartex Capabilities

24 Smartex products  Shirt (commercialized) with ECG and respiratory rate sensors.  Jumpsuit/pants with position sensors.

25 Products  Bed sheet (ECG, Resp Rate, Movement)  Elbow Sleeve (EMG, FES in development)  Glove (conductive elastomers, microbubbles for force measurement in development)

26 TREMOR PROJECT Prof. Jose Pons

27 TREMOR Project  Consortium of 8 European partners  Prof. José L. Pons (Project Coordinator), Consejo Superior de Investigaciones Científicas, Madrid, Spain along with 8 other European institutions  “An ambulatory BCI-driven tremor suppression system based on functional electrical stimulation”  “Tremor is most common movement disorder”  Managed with drugs, surgery (thalamotomy), and deep brain stimulation  Treatments are ineffective in 25% of patients

28 TREMOR PROJECT  Uses EEG and EMG along with IMUs to detect voluntary motion and tremor, using a sensor fusion approach  Use FES to either  Cancel tremor with out-of- phase stimulation  Stiffen the limb by co- contraction, to reduce tremor amplitude  Project at an early stage  Interesting use of FES making use of wearable sensors

29 UNIVERSITY OF TWENTE - MIRA Prof. Peter Veltink

30 Wearable Motion Analysis Laboratory

31 Human Movement Sensing  Inertial & magnetic sensors  10+ years of research  Now commercially available (Xsens)  Utilized in peer- reviewed publications  Enables community, institution, and home based evaluations

32 Monitoring Dynamic Interactions  Foot – Ground interaction  Instrumented shoe Two 6 DOF sensors 2 inertial sensors  Hand – object  In development

33 Instrumented Shoe  Ground Reaction Forces  Center of Mass Leidtke et. al., 2007 Schepers et al, 2009


35 Company Overview  Founded 10 years ago - University of Twente spin-off.  Focus is 3D motion tracking.  65 employees with 50% in research & development.  Focus is on 3 industries: 1) Industrial applications (unmanned vehicles), 2) Entertainment/training & simulation (movie special effects and video games), and 3) Movement science (how they started).

36 First Generation Sensor Technology First Generation Sensor  Real-time motion capture system.  Wired suit with power packs required.  Usable indoors or outdoors (difficult for video motion capture) with no marker occlusion issues.  Integration drift an issue for position estimates.

37 Second Generation Sensor Technology Second Generation Sensor  Real-time motion capture.  No wires or power packs required.  Increased accuracy.  Usable indoors or outdoors with no occlusion issues.  Integration drift resolved through UWB RF technology. Recharge Station UWB RF Receiver

38 Wearable Technology Gaps  Technology is not yet reliable for enough safety applications  EKG applications will need to be as good as standard electrodes to get traction  Kinematic technology not yet accurate enough for precise research applications (gait lab)  Xsens (1/10 th level of accuracy)

39 Wearable Technology Gaps  System integration not yet adequate for commercialization and clinical application  Technical and data security issues  Wellness vs. medical applications  Unclear if end users are adequately involved in the design process

40 Conclusions  Wearable sensors hold great promise to:  Improve diagnostics  Monitor treatment  Enhance research outcomes  Increase independence and participation  Reduce healthcare costs  However, technology is only in its “second generation”  Will need to improve accuracy, reliability and system integration for true translation to occur

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