Implementation of Fall Detection System Based on Data Fusion Technology

This paper mainly discusses a fall detecting method for the elderly, implements the wireless positioning and automatic alarm function. The system is designed with low cost Micro-Electro-Mechanical System (MEMS) inertial measurement unit to measures activities data of the elderly people, which has achieved an accurate attitude determination by Kalman filter for the multi-sensor data fusion algorithm, and transfer information to remote medical monitoring system platform by CDMA network, it makes the elderly get treatment in time after the fall. The experiments show that the system can accurately detect the elderly falling, send out alarms and positioning after a fall, its applying will provide a new security guarantee for the elderly health.