A machine learning approach to fall detection algorithm using wearable sensor

Chia Yeh Hsieh, Chih Ning Huang, Kai Chun Liu, Woei Chyn Chu, Chia Tai Chan

研究成果: Conference contribution同行評審

28 引文 斯高帕斯(Scopus)

摘要

Falls are the primary cause of accidents for the elderly in living environment. Falls frequently cause fatal and non-fatal injuries that are associated with a large amount of medical costs. Reduction hazards in living environment and doing exercise for training balance and muscle are the common strategies for fall prevention. But falls cannot be avoided completely; fall detection provides the alarm in time that can decrease the injuries or death caused by no rescue. We propose machine learning-based fall detection algorithm using multi-SVM with linear, quadratic or polynomial kernel function, and k-NN classifier. Eight kinds of falling postures and seven types of daily activities arranged in the experiment are used to explore the performance of the machine learning-based fall detection algorithm. The emulated falls were performed on a soft mat by ten healthy young subjects wearing protectors. The k-nearest neighbor method with 0.1 second window size has the highest accuracy, which is 96.26%. The results show that the proposed machine learning fall detection algorithm can fulfill the requirements of adaptability and flexibility for the individual differences.

原文English
主出版物標題Proceedings of the IEEE International Conference on Advanced Materials for Science and Engineering
主出版物子標題Innovation, Science and Engineering, IEEE-ICAMSE 2016
編輯Teen-Hang Meen, Stephen D. Prior, Artde Donald Kin-Tak Lam
發行者Institute of Electrical and Electronics Engineers Inc.
頁面707-710
頁數4
ISBN(電子)9781509038695
DOIs
出版狀態Published - 2 2月 2017
事件2016 IEEE International Conference on Advanced Materials for Science and Engineering, IEEE-ICAMSE 2016 - Tainan, Taiwan
持續時間: 12 11月 201613 11月 2016

出版系列

名字Proceedings of the IEEE International Conference on Advanced Materials for Science and Engineering: Innovation, Science and Engineering, IEEE-ICAMSE 2016

Conference

Conference2016 IEEE International Conference on Advanced Materials for Science and Engineering, IEEE-ICAMSE 2016
國家/地區Taiwan
城市Tainan
期間12/11/1613/11/16

指紋

深入研究「A machine learning approach to fall detection algorithm using wearable sensor」主題。共同形成了獨特的指紋。

引用此