Fall body detection algorithm based on tri-accelerometer sensors

Abstract

In this paper a fall body detection system for a smartphone device is proposed. Its embedded tri-accelerometer sensor was utilized to collect the information about the body motion used by a real-time Pose Body Model (PBM) identified by an Extended Kalman filter algorithm. The PBM supply an estimate about the vertical pose angle value and a neural network is used to detect body fall incidents. Moreover, an automatic Multimedia Messaging Service (MMS) will be sent to a central of vigilant where additional information including the time and the GPS coordinates, reports the suspected fall location.