Technology for Early Health Change Detection Presentation - US Ignite Application Summit 2013

1. 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, FAAN
Curators’ Professor, Sinclair School of Nursing
Executive Director, Aging In Place Project
University of Missouri

2. Squaring the Life Curve
Current trend
With proactive care
Functional Decline
Time

3. Video Introduction

4. Change in bathroom activity at night  UTI
midnight
7 am
11 pm
Health alert generated

5. Case Study: Depression
Aug.18 –Sept. 18,2009 Mar.26 –April 25,2010 Oct.1 –Oct. 31,2010
12am
7am
11pm
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

6. ER visit
Hospitalization
Health Alert
26 days before ER40 days before ER
Bed sensor data leading to a Cardiac event
Retrospective analysis

7. Embedded Bed Sensor for In-Home Use

8. Hydraulic Bed
Sensor
Finger Sensor
Beat to beat
interval
HBS
Finger
Sensor15 units deployed

9. Kinect SDK is not used
Segment person in depth image
Project to 3D, segment, and track
Log:
walking
speed, height, stride time &
stride length
In-Home Gait Analysis with Kinect

10. Two clusters for
two residents
Grandchildren
In-Home Gait Analysis 24 hrs/day
Trend in shorter footsteps
indicating dementia onset

11. 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

12. Squaring the Life Curve
Current trend
With proactive care
Functional Decline
Time
$$$$$
QoL
Better
healthcare
www.eldertech.missouri.edu
Funded in part by
NSF US Ignite
Initiative