Dementia Management IoT System
SAM3 (Sensors and Analytics for Monitoring Mobility and Memory) is a collaboration between uOttawa’s Bruyère Research Institute and Carleton University. Given 2 weeks, the objective was create a integrated physical and digital system to address some of the key aspects of night time wandering for residents at Bruyère’s continuous care facilities.
Unpredictable night time wandering, unattended cooking fires, falling and elopement are aspects that affect persons of dementia and their caregivers. Continuous supervision and care is often required to support persons with dementia, limiting their personal independence. Bruyère Research Institute's SAM3 demo suite showcases the possibilities of current technology-based solutions and services for older adults.
To better empathize for users, a realistic context was selected to help develop solutions for.
Residing in room 318 of Bruyère’s retirement continuing care facility is a couple - one who is autonomous and the other suffers from dementia. Developing in partnership with group members, we researched on various aspects of living with persons of dementia.
It began with research into existing products and technologies to help persons with dementia. Conceptual sketches were developed alongside to explore the possible device enclosures and settings. From the research and concept development, I decided to focus my physical system on the aspect of falling.
Diving into the aspect of falling, it was discovered that dementia patents are five times more likely to fall than older people who do not have cognitive impairment . Existing fall detection systems in the market often require continuous wear devices or require privacy invasive methods of detecting like cameras. Outlined in a scientific journal written in 2009 demonstrates new proof of concept for automatic fall detection of elderly people using an advanced vibration and sound algorthim.
A mood board was developed as a group to create a cohesive design language for the team’s products and integration app.
Developed on Figma, the 'Zone' app features an intuitive and easy to use interface that allows caregivers and or residence staff to setup their devices based on their floor plan and be notified of the room location in an event of a detection. Part of having a fall detector is being notified the instant your loved ones fall. The integration with the Zone app allows the device to notify caregivers when a fall is detected, giving live updates with the continuing care facilities.
The fall detection device utilizes internal microphones and accelerometers that provides constant real time data that are processed and detected internally by algorithms described in the scientific journal. Once a fall is detected, a virtual assistant will ask if they are ok, if no response is made within 30 seconds a help call will be sent out primary contacts linked in the Zone app.
To help illustrate the system's function, a scaled model of Bruyère's continuous care room was built with placement of physical devices and their interaction with the surrounding environment.
 - Shaw, Fiona. (2003). Falls in Older People with Dementia. Geriatrics & Aging, p 37-40. Retrieved March 2019