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Technology for Early Health Change Detection Presentation - US Ignite Application Summit 2013
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Technology for Early Health Change Detection
MARJORIE SKUBIC, PHD Professor, Electrical and Computer Engineering
Director, Center for Eldercare and Rehabilitation Technology
MARILYN J. RANTZ, PHD, RN, FAANCurators’ Professor, Sinclair School of Nursing
Executive Director, Aging In Place Project
University of Missouri
Squaring the Life Curve
Func
tiona
l Abi
lity
Current trendWith proactive care
Functional Decline
Time
Video Introduction
Change in bathroom activity at night UTI
midnight
7 am
11 pm
Health alert generated
Case Study: DepressionAug. 18 – Sept. 18, 2009 Mar. 26 – April 25, 2010 Oct. 1 – Oct. 31, 2010
12 am
7 am
11 pm
Depression managed & followed by a geriatric psychiatrist
After personal losses resident reported low energy, had trouble eating, and stopped going to the dining room
After intervention, resident’s activity pattern increased
ER visitHospitalization
Health Alert26 days before ER40 days before ER
Bed sensor data leading to a Cardiac event
Retrospective analysis
Embedded Bed Sensor for In-Home Use
Hydraulic Bed Sensor
Finger Sensor
Beat to beatinterval
HBS FingerSensor15 units deployed
Kinect SDK is not usedSegment person in depth image
Project to 3D, segment, and track
Log:walking speed, height, stride time & stride length
In-Home Gait Analysis with Kinect
Two clusters for two residents
Grandchildren
In-Home Gait Analysis 24 hrs/day
Trend in shorter footsteps indicating dementia onset
Why US Ignite?
• Extend to private homes in the community• More flexibility for interactive interfaces
and new capabilities• New options to provide improved security• Reduce costs by using US Ignite style local server
Squaring the Life CurveFu
nctio
nal A
bilit
y
Current trendWith proactive care
Functional Decline
Time
$$$$$QoL
Betterhealthcare
www.eldertech.missouri.edu
Funded in part by NSF US Ignite
Initiative