@inproceedings{72857da93a2c4f20a6f9cc22a5245cd6,
title = "Quantitative assessment based on kinematic measures for knee osteoarthritis rehabilitation exercise analysis",
abstract = "Knee osteoarthritis (OA) is one the common degenerative joint disease and major cause of disabilities in elder groups. Physical rehabilitation exercise is one of the common non-drug therapies for OA. Typically, knee OA patient is asked to perform rehabilitation exercise continuously in home environment after 6 weeks in the clinic. However, there are some issues should be tackled while OA patients perform rehabilitation exercise without supervision of physical therapist, such as improper postures in rehabilitation exercise, low adherence, suffers the problems of manual errors and individual variance between different raters. In this paper, we propose a quantitative assessment approach based on kinematic-based parameter groups for knee osteoarthritis rehabilitation exercise analysis. The results show the utilized indices could reflect the rehabilitation exercise performance during program.",
keywords = "knee osteoarthritis, quantitative assessment, rehabilitation analysis, wearable sensor",
author = "Jiang, {Huei Lin} and Hsieh, {Chia Yeh} and Liu, {Kai Chun} and Hsu, {Steen J.} and Chan, {Chia Tai}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 4th IEEE International Conference on Applied System Innovation, ICASI 2018 ; Conference date: 13-04-2018 Through 17-04-2018",
year = "2018",
month = jun,
day = "22",
doi = "10.1109/ICASI.2018.8394413",
language = "English",
series = "Proceedings of 4th IEEE International Conference on Applied System Innovation 2018, ICASI 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "907--909",
editor = "Lam, {Artde Donald Kin-Tak} and Prior, {Stephen D.} and Teen-Hang Meen",
booktitle = "Proceedings of 4th IEEE International Conference on Applied System Innovation 2018, ICASI 2018",
address = "United States",
}