Creation and validation of fall detection algorithms for seniors based on sensor data

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In this project we are aiming to begin developing a fall detection algorithm to address the need of our industrial partner Azure WearTech Inc. (AWT). This algorithm will be integrated with a wearable device and help the caregivers to find the location of the injured people in fall incidences. Falls by seniors are the leading cause of injuries and hospitalizations worldwide and the injuries have short and long-term consequences. Several studies and reports conducted by health organization indicate senior falls and its related injuries as significant and growing problem. Improving the health standard in retirement home facilities, the interest of federal and provincial health organizations to promote independent living, and growing number of elderly population, combined with the high rate of falls and the cost incurred by the resulting injuries indicates that there is a clear need for developing devices and systems to help the situation. In this project we are planning to develop a novel fall detection system. We are also planning to collect data from volunteer seniors to better train our algorithm. We are also planning to monitor the performance of the algorithm to identify potential problems. The outcome of this research will be an algorithm which has the ability to detect falls for our industrial partner. This project will have financial benefits for our technology user corporation, and bring short and long-term social and economical benefits to Canada in the area of public health. In addition to the these benefits, the research empowered by this proposal will lead to training of highly qualified personnel in high demanding health and applied science areas.