Aip eldertech-june-2013-us-ignite-6-24b

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Aip eldertech-june-2013-us-ignite-6-24b

  1. 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. 2. Squaring the Life Curve Current trend With proactive care Functional Decline Time
  3. 3. Video Introduction
  4. 4. Change in bathroom activity at night  UTI midnight 7 am 11 pm Health alert generated
  5. 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. 6. ER visit Hospitalization Health Alert 26 days before ER40 days before ER Bed sensor data leading to a Cardiac event Retrospective analysis
  7. 7. Embedded Bed Sensor for In-Home Use
  8. 8. Hydraulic Bed Sensor Finger Sensor Beat to beat interval HBS Finger Sensor15 units deployed
  9. 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. 10. Two clusters for two residents Grandchildren In-Home Gait Analysis 24 hrs/day Trend in shorter footsteps indicating dementia onset
  11. 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. 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

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