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Home Health Care and Assisted Living Professor John A. Stankovic Department of Computer Science University of Virginia.

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Presentation on theme: "Home Health Care and Assisted Living Professor John A. Stankovic Department of Computer Science University of Virginia."— Presentation transcript:

1 Home Health Care and Assisted Living Professor John A. Stankovic Department of Computer Science University of Virginia

2 Themes Unobtrusive and wireless sensor devices and networks Support for many different medical problems Individual “products” Complete “systems”

3 Outline Examples of Technology for Medicine –Home Health Care and Assisted Living – Stankovic et. al. –Gait Monitoring – Weaver et. al. –Body Sensor Networks – Lach et. al. –Smart Walker – Russell et. al.

4 The Problems Home Health Care (Large Scale) Assisted Living Facilities

5 Smart Living Space

6 The SEAS Vision Flexible targeting of care to a person’s health condition Environmental and Physiological Data Longitudinal Studies

7 The SEAS–Medicine Vision Flexible targeting of care to a person’s health condition –Stroke, Parkinsons, Diabetes, Dementia, … Environmental and Physiological Data (Define new) Longitudinal Studies

8 With Harvard

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10 With MARC UVA Medical School

11 SATIRE * With the Univ. of Illinois

12 Other Sensor Data Physiological –Pulse –SpO2 –ECG –Blood Pressure –Weight –(Dust/Pollen) Activities –Walking –Sitting –Falling –…

13 GaitMate: Gait Analysis Mark Williams, MD, and Alfred Weaver, PhD Attach accelerometers to ankles and sacrum; wire to data recorder; next generation equipment is wireless Collect 3D motion data from four sensors as patient walks down hallway, turns around, and walks back Software analyzes waveform and automatically identifies significant events, e.g. heal strike, toe-off Physician analyzes graphs to diagnose or predict disease (e.g., Parkinson’s)

14 Body Sensor Networks for Monitoring and Assessing Movement Disorders PI: John Lach (jlach@virginia.edu) Graduate students: Adam Barth, Mark Hanson, Harry Powell Application examples –Tremor assessment for Parkinson’s Disease and Essential Tremor study, diagnosis, treatment –Gait analysis for movement disorder diagnosis and fall risk assessment –Assessing efficacy of Cerebral Palsy physical therapy treatments Key system metrics –Wearable (small, light, easy to use) –Low power (long lifetime with small battery) –Configurable (system can be adapted for specific applications) Wireless sensor node Tremor frequency domain analysis example (high energy at ~5Hz reveals tremor)

15 NSF WALKER TEAM

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17 Home Health Care and Assisted Living AlarmNet: emulated assisted living facility

18 PDA Real-Time Queries AlarmGate SW on stargate DB

19 Circadian Rhythms Circadian activity rhythm per room for 70 days

20 Behavioral Deviation Life Habits at-home Learning period Diurnal/nocturnal activity

21 Summary/Vision Tailored to Patient Health –Stroke, Parkinsons, Diabetes, Incontinence, … Improve Health Care Improve Quality of Life Reduce Medical Errors Continuous Monitoring –More natural settings –More complete Collect Data for Longitudinal Studies

22 Summary/Vision Unobtrusive body networks (smart clothes) Seemlessly integrate into larger wireless sensor network Combine Environment, Activities and Individual Physiological Data Provide continuous 24/7 care, if needed and as needed Detect anomalies and react Learn correlations to prevent disease Effectiveness of treatment


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