Using Wearable Sensor and NMF Algorithm to Realize Ambulatory Fall Detection

Abstract

Falls in the elderly people often cause serious physical injury, result in fracture, cerebral haemorrhage, even death. To find falls as earlier as possible is very important to rescue the subjects and facilitate the rehabilitation in the future. In this paper, we use a wearable tri-axial accelerometer to monitor the movement parameters of human body, and propose a novel fall detection algorithm based on non-negative matrix factorization (NMF). The input vectors are the acceleration sequences of the transverse section and the vertical axial of human body, and these vectors are decomposed via NMF. And then, a k-nearest neighbor method is applied to determine whether a fall occurred. The results show that this method can detect the falls effectively.