Wearable sensing technology uses sensors to detect body information, which sends monitoring and control exercise information to a receiver through wireless transmission. This study proposes a low power consumption wearable shoe type sensing module for fall detection. An algorithm for directional identification of footsteps is designed to detect both the motion state and movement direction of footsteps. The information is transmitted to the healthy exercise service application of a mobile phone through wireless transmission, where consumed calories are calculated by the motion state, allowing the user to observe their health status at any time. The most significant cause of sensor energy consumption is massive data communication; therefore, this study effectively applies few parameters, and uses the action segment classified signal, as inspired by continuous speech recognition, to optimize the parameters, in order to improve energy loss by reducing data transfer.
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications