Next Article in Journal
Sol-Gel Deposition of Iridium Oxide for Biomedical Micro-Devices
Previous Article in Journal
Compressive SAR Imaging with Joint Sparsity and Local Similarity Exploitation
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(2), 4193-4211; doi:10.3390/s150204193

Wearable Sensor-Based Rehabilitation Exercise Assessment for Knee Osteoarthritis

1
Department of Biomedical Engineering, National Yang-Ming University, 155, Li-Nong St., Sec.2, Peitou, Taipei 11221, Taiwan
2
Department of Orthopaedic Surgery, Taichung Veterans General Hospital, 1650 Taiwan Boulevard Sect. 4, Taichung 40705, Taiwan
*
Author to whom correspondence should be addressed.
Received: 14 October 2014 / Accepted: 26 January 2015 / Published: 12 February 2015
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [2065 KB, uploaded 12 February 2015]   |  

Abstract

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. View Full-Text
Keywords: knee joint rehabilitation exercise; wearable sensor; rehabilitation assessment system knee joint rehabilitation exercise; wearable sensor; rehabilitation assessment system
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Chen, K.-H.; Chen, P.-C.; Liu, K.-C.; Chan, C.-T. Wearable Sensor-Based Rehabilitation Exercise Assessment for Knee Osteoarthritis. Sensors 2015, 15, 4193-4211.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top