Tony Tam Candidate MHSc. Clinical Engineering Tony.Tam@utoronto Contributions from:

1. Intelligent Homes and Supportive Environments Tony Tam Candidate MHSc. Clinical Engineering Tony.Tam@utoronto.ca Contributions from: Professor Alex Mihailidis Tracy Lee Brent Carmichael Jennifer Boger

2. Think outside the box! Homes Hospital (BOX)

3. Presentation Overview • Objectives of Intelligent Homes and Supportive Environments • Basic Intelligence • Environmental control • Safety and Security • Supportive Environments • Health Monitoring • Emergency Response • Home Telehealth • Automated prompting for rehabilitation

4. Objectives of Intelligent Homes and Supportive Environments • Support older adults who want to remain in their own homes for as long as possible • Allow them to maintain control over their environments and activities of daily living (ADL) for a sense of well-being and dignity. • A concept known as “Aging In Place”

5. Difficulties • Ensuring safety, especially for older adults who live alone and/or have a mental disability Common causes of accidental injury for older adults in the home are: • Falls (1 in 3 experience a fall over the course of a year), (Johnson et al., 2001) • Poisoning from medication, gases, and vapours • Burns and scalds from cooking and hot water Professor Alex Mihailidis, GERO830 - Human Factors, Technology and Safety

6. Opportunities for Supporting Older Adults • Provide an environment that is constantly monitored to ensure safety • Automate specific tasks that an individual is unable to perform • Alert helpers or caregivers should the occupant be in difficulties • Enable and empower the user • Facilitate the rehabilitation of individuals. Professor Alex Mihailidis, GERO830 - Human Factors, Technology and Safety

7. Basic Intelligence - Environmental Control The Adaptive House • Energy control • Automatic heating • Humidity control • Automatic screens and curtains • Automatic lighting at night • Automatic sprinklers http://www.cs.colorado.edu/~mozer/house/ • The Adaptive House, University of Colorado • Uses artificial neural networks to learn the patterns and desires of its occupants • Automatically adjusts heating, ventilation, air conditioning, water heater, and interior lighting.

8. Basic Intelligence - Safety & Security • Security entry for health care personnel • Medication Adherence • Intruder alarms • Smoke alarms • Automatic shut off of stoves • Water temperature regulation Professor Alex Mihailidis, GERO830 - Human Factors, Technology and Safety

9. Basic Intelligence – Safety & Security • Water level monitor • Normal use - unless flood levels reached • Prevent flooding and wasted water http://www.bath.ac.uk/bime/bath_monitor_proj.htm

10. Supportive Environments

11. Supportive Environments - ADL One of the biggest predictors of successful aging-in-place is the independent completion of Activities of Daily Living (ADL)

12. Supportive Environments – Health Monitoring • Gloucester Smart Home from the Bath Institute of Medical Engineering • Use of various sensors to detect which task a person is completing, and learns about the person’s daily routine • Notices variations over time, possibly indicating declining health

13. Supportive Environments – Cognitive Support Aware Home, Georgia Tech Help older adults complete activities of daily living: • Take medication • Locate lost items (RFID) • Reminders if they become distracted, (e.g. recipe reminders) http://www.cc.gatech.edu/fac/irfan/presentations/cfh2001_files/frame.htm

14. Supportive Environments - Connected • Provides electronic snapshots and portraits of the person’s activities • Peace of mind to allow aging family members to age in place (like next door neighbor checking in) http://www.cc.gatech.edu/fce/ecl/projects/dfp/index.html

15. Emergency Response • Actively monitor and ensure health and safety • Detect various emergency situations • The person becoming ill • Falling and becoming injured • Determine appropriate response

16. Existing Emergency Response Solutions Call Buttons and Communicator Worn Fall Detector http://www.lifelinesys.com/howworks/index.php http://ntec.org.uk/gm2.doc

17. Detection of Falls http://www.computing.dundee.ac.uk/projects/supportiveenvironments/

18. Detection of Falls (Intelligent Assistive Technology and Systems Lab)

19. Active Health Monitoring • Stroke, Heart Attack • Injury (burns, scalds) • Poisoning (medication, smoke) • Research: wearable sensors, monitoring ADL • Is this person reading, asleep, unconscious? http://www.computing.dundee.ac.uk/projects/supportiveenvironments/

20. Home Telehealth • Comfort of individual’s own homes • Less time driving for nurses, more time visiting http://hth.marchnetworks.com/pdf/hthbackgrounder.pdf

21. Tele-Rehabilitation Maintenance of a rehabilitation program such as exercises normally declines with time, especially if the patient is left to their own motivation. • Range of motion glove • Grip meter • pinch meter

22. Automated Prompting Devices for People with Dementia • Greatest predictor of successful aging-in-place is the independent completion of ADL activities • Assist users with ADL through sensing and automated prompting • Hand Washing, Toileting Mihailidis, Carmichael, and Boger. The use of computer vision in an intelligent environment to support aging-in-place, safety, and independence in the home. 2003

23. Thank you! • For more information on current research at the • Intelligent Assistive Technology and Systems Lab: • Intelligent environments and smart homes for older adults • Automated prompting devices for people with dementia • Home monitoring and emergency response systems • Applications of ubiquitous and pervasive computing in healthcare http://www.ot.utoronto.ca/iatsl/

24. References Adapted from Professor Alex Mihailidis’ course: GERO830 - Human Factors, Technology and Safety Dhurjaty, S. (2001). Challenges of Telerehabilitation in the Ho me Environment. In:Proceedings of the State of the Science Conference on Telerehabilitation , 89 – 93. Johnson, M., A. Cusick, et al. (2001). "Home-Screen: A short scale to measure fall risk in the home." Public Health Nursing 18(3): 169-177. Ogawa, M., Ochiai, S., Shoji, K., Nishihara, M., Togawa, T. (2000). An attempt of monitoring daily activities at home. Presented at: World Congress on Medical Physics and Biomedical Engineering , Melville: American Association of Physicists in Medicine.