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1 Tony Tam Candidate MHSc. Clinical Engineering Contributions from: Professor Alex Mihailidis Tracy Lee Brent Carmichael Jennifer.

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Presentation on theme: "1 Tony Tam Candidate MHSc. Clinical Engineering Contributions from: Professor Alex Mihailidis Tracy Lee Brent Carmichael Jennifer."— Presentation transcript:

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

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

3 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 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 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 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 7 Basic Intelligence - Environmental Control Energy control Automatic heating Humidity control Automatic screens and curtains Automatic lighting at night Automatic sprinklers 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. The Adaptive House

8 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 9 Basic Intelligence – Safety & Security Water level monitor Normal use - unless flood levels reached Prevent flooding and wasted water

10 10 Supportive Environments

11 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 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 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)

14 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)

15 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 16 Existing Emergency Response Solutions Call Buttons and CommunicatorWorn Fall Detector

17 17 Detection of Falls

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

19 19 Active Health Monitoring Stroke, Heart Attack Injury (burns, scalds) Poisoning (medication, smoke) Research: wearable sensors, monitoring ADL Is this person reading, asleep, unconscious?

20 20 Home Telehealth Comfort of individual’s own homes Less time driving for nurses, more time visiting

21 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 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 23 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 Thank you!

24 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): 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.


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