Human motion identification for rehabilitation exercise assessment of knee osteoarthritis

Po Chun Huang, Kai Chun Liu, Chia Yeh Hsieh, Chia Tai Chan

研究成果: Conference contribution同行評審

8 引文 斯高帕斯(Scopus)

摘要

Osteoarthritis (OA) is one of the majority of chronic lower limb musculoskeletal conditions, affecting approximately 15% of the population. Rehabilitation exercise has been considered as a common and essential medical treatment for mild to moderate stages of knee OA. However, there are some issues and challenges should be tackled while OA patient performs rehabilitation exercise without supervision of therapist, such as improperly implement rehabilitation exercise and patient adherence. The objective of this study is to propose a machine learning-based human motion identification system to automatically classify rehabilitation types and the motion states. The overall accuracy for types recognition is 100% and for motion identification is 97.7%. The results show that the feasibility of the proposed human motion identification algorithm for home-based rehabilitation.

原文English
主出版物標題Proceedings of the 2017 IEEE International Conference on Applied System Innovation
主出版物子標題Applied System Innovation for Modern Technology, ICASI 2017
編輯Teen-Hang Meen, Artde Donald Kin-Tak Lam, Stephen D. Prior
發行者Institute of Electrical and Electronics Engineers Inc.
頁面246-249
頁數4
ISBN(電子)9781509048977
DOIs
出版狀態Published - 21 7月 2017
事件2017 IEEE International Conference on Applied System Innovation, ICASI 2017 - Sapporo, Japan
持續時間: 13 5月 201717 5月 2017

出版系列

名字Proceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017

Conference

Conference2017 IEEE International Conference on Applied System Innovation, ICASI 2017
國家/地區Japan
城市Sapporo
期間13/05/1717/05/17

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