A portable fall detection and alerting system based on k-NN algorithm and remote medicine

This paper presents information on a portable fall detection and alerting system mainly consisting of a custom vest and a mobile smart phone. A wearable motion detection sensor integrated with tri-axial accelerometer, gyroscope and Bluetooth is built into a custom vest worn by elderly. The vest can capture the reluctant acceleration and angular velocity about the activities of daily living (ADLs) of elderly in real time. The data via Bluetooth is then sent to a mobile smart phone running a fall detection program based on k-NN algorithm. When a fall occurs the phone can alert a family member or health care center through a call or emergent text message using a built in Global Positioning System. The experimental results show that the system discriminates falls from ADLs with a sensitivity of 95%, and a specificity of 96.67%. This system can provide remote monitoring and timely help for the elderly.