Human falling detection based on accelerometer
一种基于加速度传感器的人体跌倒识别方法

In order to lessen the injury of elder people caused by falling, and to recognize falling timely and effectively, this paper proposed a method to identify human falling based on a tri-axis accelerometer. It put the accelerometer on the waist to collect the changing data of acceleration from human motions, trained the parameters of HMM by using the data from activities in daily life. By making use of the special characteristic of few activities of elder people, it detected suspected falling according to the matching degree between observation data and HMM. And then, it calculated body tile angle in a short time to detect human lying, which helped to complete the recognition. This method solved the problem of the inadequate training samples of falling data in daily life and improved the distinction of some similar behaviours. Simulation results show that this method can not only effectively identify human falling, but also improve the accurate rate.