Picking a human fall detection algorithm for wrist-worn electronic device
Illia Kukharenko, Volodymyr Romanenko · 2017 IEEE First Ukraine Conference on Electrical and Computer Engineering (UKRCON) · 2017
Nation aging raises a problem of elderly health care and this problem will only grow stronger next decades. Preventive and remote care for seniors come to the fore as the solution to lower the number of potential patients in clinics and to reduce the cost of medication in case of accidents by providing first aid in time. Human fall is a source of danger in any age and, especially for older people. It can become a cause of injury itself and it can also be a result of dangerous event in human organism. That's why human fall detection is significant. This paper describes a first phase of research dedicated to developing a fall detection algorithm for a wrist-worn wearable device. Comparison and analysis of existing algorithms and solutions on market is made. Hardware setup for human fall detection is built and tested. Live tests on volunteers are performed to evaluate accuracy of chosen type of algorithm. Also algorithm is tested during daily activity to determine most fall-similar actions, and work out a way to distinguish those from true fall.