Grant: Idea to Innovation

We propose to develop a prototype of contactless monitoring technology that will detect falls and estimate breathing of elderly people in retirement homes. Some of these people are chronically ill, infirm or unable to take care of themselves and they very often fall which results in medical distress. In nursing or retirement homes, a limited number of nurses is available to monitor relatively large number of residents. In this kind of setting, there is a need for a system that would further improve the nurse's ability to respond appropriately to critical events such as a fall as quickly as possible. Wearable devices are commonly used for that purpose; however residents might take them off while going for example to the bathroom which is the area where most of falls occur. The key requirement of our systems is to allow for continuous monitoring without any impact on daily routines. In this project, we propose to use ultra-wide band radar for monitoring falls, activities and breathing in confined spaces such as bathrooms and bedrooms in retirement homes. The team at the University of Ottawa has developed a suite of algorithms for breathing rate estimation, location of the subject and classification of postures under realistic conditions using different types of radars. Funding from this I2I project will allow us to develop and deploy our first prototype in the retirement home. We will connect our radar to the nurse call system as well as to the cloud making it a part of retirement home electronic system and allowing it to scale. If fall is detected, the nurses will be notified through nurse call system. The technology has the potential to generate economic benefits by providing new revenue streams for retirement home integrators and radar manufacturers in Canada. The project is important for Canada because it will result in improving quality of life of the people that are at increased risk of fall or injury. In addition, it has a potential to result in significant savings in health-care costs because it will allow medical workers to detect events in progress, such as falls of elderly people, and to react on time.