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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 ([email protected])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