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Wearable Sensor-Based Rehabilitation Exercise Assessment for Knee Osteoarthritis

Since the knee joint bears the full weight load of the human body and the highest pressure loads while providing flexible movement, it is the body part most vulnerable and susceptible to osteoarthritis. In exercise therapy, the early rehabilitation stages last for approximately six weeks, during whi...

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Autores principales: Chen, Kun-Hui, Chen, Po-Chao, Liu, Kai-Chun, Chan, Chia-Tai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4367405/
https://www.ncbi.nlm.nih.gov/pubmed/25686308
http://dx.doi.org/10.3390/s150204193
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author Chen, Kun-Hui
Chen, Po-Chao
Liu, Kai-Chun
Chan, Chia-Tai
author_facet Chen, Kun-Hui
Chen, Po-Chao
Liu, Kai-Chun
Chan, Chia-Tai
author_sort Chen, Kun-Hui
collection PubMed
description Since the knee joint bears the full weight load of the human body and the highest pressure loads while providing flexible movement, it is the body part most vulnerable and susceptible to osteoarthritis. In exercise therapy, the early rehabilitation stages last for approximately six weeks, during which the patient works with the physical therapist several times each week. The patient is afterwards given instructions for continuing rehabilitation exercise by him/herself at home. This study develops a rehabilitation exercise assessment mechanism using three wearable sensors mounted on the chest, thigh and shank of the working leg in order to enable the patients with knee osteoarthritis to manage their own rehabilitation progress. In this work, time-domain, frequency-domain features and angle information of the motion sensor signals are used to classify the exercise type and identify whether their postures are proper or not. Three types of rehabilitation exercise commonly prescribed to knee osteoarthritis patients are: Short-Arc Exercise, Straight Leg Raise, and Quadriceps Strengthening Mini-squats. After ten subjects performed the three kinds of rehabilitation activities, three validation techniques including 10-fold cross-validation, within subject cross validation, and leave-one-subject cross validation are utilized to confirm the proposed mechanism. The overall recognition accuracy for exercise type classification is 97.29% and for exercise posture identification it is 88.26%. The experimental results demonstrate the feasibility of the proposed mechanism which can help patients perform rehabilitation movements and progress effectively. Moreover, the proposed mechanism is able to detect multiple errors at once, fulfilling the requirements for rehabilitation assessment.
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spelling pubmed-43674052015-04-30 Wearable Sensor-Based Rehabilitation Exercise Assessment for Knee Osteoarthritis Chen, Kun-Hui Chen, Po-Chao Liu, Kai-Chun Chan, Chia-Tai Sensors (Basel) Article Since the knee joint bears the full weight load of the human body and the highest pressure loads while providing flexible movement, it is the body part most vulnerable and susceptible to osteoarthritis. In exercise therapy, the early rehabilitation stages last for approximately six weeks, during which the patient works with the physical therapist several times each week. The patient is afterwards given instructions for continuing rehabilitation exercise by him/herself at home. This study develops a rehabilitation exercise assessment mechanism using three wearable sensors mounted on the chest, thigh and shank of the working leg in order to enable the patients with knee osteoarthritis to manage their own rehabilitation progress. In this work, time-domain, frequency-domain features and angle information of the motion sensor signals are used to classify the exercise type and identify whether their postures are proper or not. Three types of rehabilitation exercise commonly prescribed to knee osteoarthritis patients are: Short-Arc Exercise, Straight Leg Raise, and Quadriceps Strengthening Mini-squats. After ten subjects performed the three kinds of rehabilitation activities, three validation techniques including 10-fold cross-validation, within subject cross validation, and leave-one-subject cross validation are utilized to confirm the proposed mechanism. The overall recognition accuracy for exercise type classification is 97.29% and for exercise posture identification it is 88.26%. The experimental results demonstrate the feasibility of the proposed mechanism which can help patients perform rehabilitation movements and progress effectively. Moreover, the proposed mechanism is able to detect multiple errors at once, fulfilling the requirements for rehabilitation assessment. MDPI 2015-02-12 /pmc/articles/PMC4367405/ /pubmed/25686308 http://dx.doi.org/10.3390/s150204193 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chen, Kun-Hui
Chen, Po-Chao
Liu, Kai-Chun
Chan, Chia-Tai
Wearable Sensor-Based Rehabilitation Exercise Assessment for Knee Osteoarthritis
title Wearable Sensor-Based Rehabilitation Exercise Assessment for Knee Osteoarthritis
title_full Wearable Sensor-Based Rehabilitation Exercise Assessment for Knee Osteoarthritis
title_fullStr Wearable Sensor-Based Rehabilitation Exercise Assessment for Knee Osteoarthritis
title_full_unstemmed Wearable Sensor-Based Rehabilitation Exercise Assessment for Knee Osteoarthritis
title_short Wearable Sensor-Based Rehabilitation Exercise Assessment for Knee Osteoarthritis
title_sort wearable sensor-based rehabilitation exercise assessment for knee osteoarthritis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4367405/
https://www.ncbi.nlm.nih.gov/pubmed/25686308
http://dx.doi.org/10.3390/s150204193
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