ORCATECH The Internet of Everything – Pervasive Computing for Health Jeffrey Kaye

1. OREGON CONNECTIONS TELECOMMUNICATIONS CONFERENCE - “Broadband: The Pulse of the Future” October 23-24, 2013, Hood River, Oregon ORCATECH The Internet of Everything – Pervasive Computing for Health Jeffrey Kaye Layton Professor of Neurology & Biomedical Engineering Oregon Center for Aging & Technology Layton Aging & Alzheimer's Disease Center Carl Richards kaye@ohsu.edu

2. Current Assessmentis Limited Cardinal features of health change - slowdecline punctuated with acute events - are challenging to assess with current tools and methods.

3. Assessment LimitationsInclude… • Rely on sparsely spaced, brief queries – questionnaires, phone or in-person exams. • Performed at the convenience of the assessor. • Depend on recall of events or brief snap-shots of function. • Use artificial or non-real world tests; not fun • Assumes observations recorded during the exam represent typical function • Challenged to track across the course of illness. • High inter-rater or test-to-test variability • Limited knowledge of other events that can significantly effect outcomes (e.g., sleep, socialization, physical activity)

4. Functional range Baseline 3 years 6 years The Greatest Challenge: Detecting Meaningful Change Early detection Change Symptoms Reported Measure

5. Path Forward: Change the Paradigm OPTIMAL HEALTH • Brief • Episodic • Clinic-based • Obtrusive • Inconvenient • Real-time • Continuous • Home-based • Unobtrusive • Ambient Pervasive Computing Wireless Technologies “Big Data” Analytics • New Discovery • New & Transformed Businesses

6. To Facilitate this Change… • Target key functions most related to QoL and highest costs that can be unobtrusively detected to change over time (e.g., cognition, gait, mood, pain, sleep, socialization). • Build upon advances in remote sensing, pervasive computing, telehealth, activity and behavior modeling creating an ambient, multi-domain home-based assessment system. • Minimize need to wear, carry or tend to devices, and especially to disrupt the person’s usual daily routine. • Increase sensitivity by continuous, multi-domain assessment.

7. Pervasive Computing Platform Elements Bed Sensors Physiological sensors Actigraphy devices Phone sensors Localization sensors Walking sensors Activity sensors Cell phone as prompting device and for location tracking Medication tracking device Door sensors PC/Kiosk/Etc.: Experience sampling; cognitive testing; social engagement; coaching Actigraphy devices Actigraphy devices Actigraphy devices Actigraphy devices Actigraphy devices Physiological sensors Physiological sensors Physiological sensors Physiological sensors Physiological sensors Bed mats Bed mats Bed mats Bed mats Bed mats Phone sensors Phone sensors Phone sensors Phone sensors Phone sensors Localization sensors Localization sensors Localization sensors Localization sensors Localization sensors Walking speed sensors Walking speed sensors Walking speed sensors Walking speed sensors Walking speed sensors Activity sensors Activity sensors Activity sensors Activity sensors Activity sensors Cell phone as prompting device and for location tracking Cell phone as prompting device and for location tracking Cell phone as prompting device and for location tracking Cell phone as prompting device and for location tracking Cell phone as prompting device and for location tracking Medication tracking device Medication tracking device Medication tracking device Medication tracking device Medication tracking device Home computer for coaching, personal use, and cognitive testing Home computer for coaching, personal use, and cognitive testing Home computer for coaching, personal use, and cognitive testing Home computer for coaching, personal use, and cognitive testing Home computer for coaching, personal use, and cognitive testing Door sensors Door sensors Door sensors Door sensors Door sensors

8. What you get: Continuous, Holistic Assessment “A Day in the Life”

9. Embedded Ambient Assessment Technologies

10. Together: A Community-wide Home-Based Assessment Platform Activity Time & Location Body Composition Gait Speed MedTracker Phone Activity Secure Internet Computer/Kiosk Activity Doors Opening/Closing Kaye et al. Journals of Gerontology: Psychological Sciences, 2011

11. Identifying change using remote assessment methods: Evidence Examples Room Transitions during a Norovirus Epidemic Intact MCI Daily Activity & Cognitive Decline

12. Total Activity: Life Space & EventAnalysis Spiral plot: The plot is a 24 hour clock representing here 8 weeks of continuous data. At the top of the clock is midnight; at the bottom is noon. Each concentric blue circle outward represents 2 weeks of time. The colors of the dots represent firings of sensors by location Living room Bedroom Bath Kitchen Computer Session

13. Norovirus Epidemic: All ill patients identified by decreased room transition events without self report -40% -34% -24% Campbell, 2011

14. Walks: From 2 to 7000 per year Photo: NYT, 2009 Hayes, 2009; Hagler, 2010; Kaye, 2012

15. Variability in walking speed and total activity differentiates MCI from cognitively normal people MCI NL • Mean age = 88 years • Mean in-home motion-activity sensing 315 ± 82 days 
Hayes et al.Alzheimer's & Dementia, 2008; 4(6): 395-405. Hayes et al. Alzheimer’s & Dementia, 2008

16. Routine home PC use over time (without formal tests or queries) detects change in those with MCI Intact MCI • Mean 1.5 hours on computer/per day at baseline month • Over time: • Less use days per month • Less use time when in session • More variable in use pattern over time Kaye, et al. 2011 Kaye, et al. Alzheimer & Dementia, 2013

17. Continuous, multi-domain assessment over timevia pervasive computing – the future norm… Improved Assessment & Outcomes Data Fusion

18. Acknowledgements: The ORCATECH Village Research Collaborators Diverse Companies Funding Sponsors

19. Additional Material

20. Direct Assessment of Everyday Cognition ORCATECH MedTracker PROSPECTIVE MEMORY Prospective memory task – probability of remembering to take medications as desired tracked using a familiar plastic pill box. vs Conventional memory task – recall a list of unrelated words. Hayes et al., Proceedings : Engineering in Medicine and Biology Soc, 2006; Leen T, et al., Technology and Aging, 2007 ; Hayes T et al. .Journal of Aging Health, 2009; Hayes T et al.Telemedicine Jounal and E-Health, 2009

21. 100 90 80 70 60 % Adherent 50 40 Median time within 53.4 mins of goal Median time within 12.0 mins of goal 30 20 10 0 Higher Cognition Lower Cognition Medication Adherence: A Sensitive Measure of Cognitive Function * Significantly worse Adherence in Lower Cognition Group • Adherence assessed with MedTracker taking a vitamin BID; target times set by seniors • Mean Age - 83 yrs • Assessed continuously x 5 wks • Based on ADAScog: Lower Cognition Group (n =18) vs Higher Cognition Group (n = 20) • Very mild cognitive change in independent elderly is associated with medication adherence • Medication adherence can be a very early marker of cognitive and functional impairment. Hayes T et al., Journal of Aging Health, 2009

22. Raw Sensor Data Direct Assessment Inference Change Detection Mobility Gait Velocity MotionDetectors Sleep Hygiene LocationEstimation LocationTracking Socialization Sleep Load Cells / Bed Sensors Depression DeparturesArrivals Contact/DoorSwitches Cognitive Decline Memory Phone Use PhoneSensors Attention ComputerInteractions Computer MedicationAdherence MedicationEvents MedicationTracker PhysicalImpairments Weight WeightScale Sensor Level Fusion Information Level Fusion

23. Mirabella Portland, a new generation of Living Laboratories

24. Weekly on-line reports provides unique insights into function: patterns of low mood “During the last week, have you felt downhearted or blue for more than three days?” N = 122; 14,566 reports (2008-2010) Seasonal Pattern of Low Mood Reports Thielke, unpublished, 2013

25. Social Engagement RCTHiroko Dodge, PI

26. Face-to-Face Internet email/VOIP Channels of Engagement Telephone