Home Health Care and

Assisted Living

Professor John A. StankovicDepartment of Computer Science

University of Virginia

Themes

• Unobtrusive and wireless sensor devices and networks

• Support for many different medical problems

• Individual “products”

• Complete “systems”

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.

The Problems

• Home Health Care

• (Large Scale) Assisted Living Facilities

Smart Living Space

The SEAS Vision

• Flexible targeting of care to a person’s health condition

• Environmental and Physiological Data

• Longitudinal Studies

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

With Harvard

With Harvard

With MARC UVA

Medical School

SATIRE

* With the Univ. of Illinois

Other Sensor Data

• Physiological– Pulse– SpO2– ECG– Blood Pressure– Weight– (Dust/Pollen)

• Activities– Walking– Sitting– Falling– …

GaitMate: Gait AnalysisMark Williams, MD, and Alfred Weaver, PhD

The initial sensor prototype

Plot of the VecMag with the analytical sample shown

Analytical sample showing the six “essential points”

Attach accelerometers to ankles and sacrum; wire to data recorder;next generation equipment is wireless

Collect 3D motion data from four sensorsas 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 orpredict disease (e.g., Parkinson’s)

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)

NSF WALKER TEAM

Home Health Care and Assisted Living

• AlarmNet: emulated assisted living facility

PDA Real-Time Queries

AlarmGate SW on stargate

DB

Circadian Rhythms

Circadian activity rhythm per room for 70 days

0

10

20

30

40

50

60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

24 hour cycle

Cir

ca

dia

n a

cti

vit

y r

hy

thm

s (

min

)

Bedroom

Kitchen

LivingroomBathroom

WC

Behavioral Deviation

Life Habitsat-home Learning

period

Diurnal/nocturnalactivity

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

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