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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
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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. |
format | Online Article Text |
id | pubmed-4367405 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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