Using wearable sensor and NMF algorithm to realize ambulatory fall detection

Authors:
Tong Zhang;Jue Wang;Liang Xu;Ping Liu
Affiliations:
Key Laboratory of Biomedical Information Engineering of Education Ministry, Xi'an Jiaotong University, Xi'an, Shaanxi, P.R. China;Key Laboratory of Biomedical Information Engineering of Education Ministry, Xi'an Jiaotong University, Xi'an, Shaanxi, P.R. China;School of Computer Science and Technology of Xidian University, Xi'an, Shaanxi, P.R. China;Key Laboratory of Biomedical Information Engineering of Education Ministry, Xi'an Jiaotong University, Xi'an, Shaanxi, P.R. China
Venue:
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
Year:
2006

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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.