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

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