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Evaluation of physical exercise for osteoarthritis of the knee through image processing technique

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dc.contributor.author Pattamaset S.
dc.contributor.author Charoenpong T.
dc.contributor.author Charoensiriwath S.
dc.date.accessioned 2021-04-05T03:01:55Z
dc.date.available 2021-04-05T03:01:55Z
dc.date.issued 2020
dc.identifier.other 2-s2.0-85084033564
dc.identifier.uri https://ir.swu.ac.th/jspui/handle/123456789/12100
dc.identifier.uri https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084033564&doi=10.1109%2fKST48564.2020.9059534&partnerID=40&md5=aab02472f38bf05e44734d9711ac300a
dc.description.abstract This research aims to automatically check the correctness of knee exercises for patients with knee osteoarthritis. The patients need to be treated by physical exercise for knee but cannot know the efficacy of physical exercise while doing at home. We developed the automatic system which processes images from knee exercising video of subject who does exercise. This system utilized of histogram analysis and skeletonization. The experimental result was tested by 17 subjects. The system verifies whether subjects do an exercise correctly or incorrectly. The overall accuracy of the exercise postures classification is 73.94%, the overall accuracy of the exercise postures correctness checking is 90.18, and the overall accuracy of the automatic system which verifies the exercise postures is 88.12%. The advantage of the purpose is the patient can do physical exercise spontaneously without attaching a device to the body and know their performance at home. © 2020 IEEE.
dc.subject Patient treatment
dc.subject Sports
dc.subject Automatic systems
dc.subject Histogram analysis
dc.subject Image processing technique
dc.subject Knee osteoarthritis
dc.subject Osteoarthritis of the knee
dc.subject Overall accuracies
dc.subject Physical exercise
dc.subject Skeletonization
dc.subject Image processing
dc.title Evaluation of physical exercise for osteoarthritis of the knee through image processing technique
dc.type Conference Paper
dc.rights.holder Scopus
dc.identifier.bibliograpycitation KST 2020 - 2020 12th International Conference on Knowledge and Smart Technology. (2020), p.127-130
dc.identifier.doi 10.1109/KST48564.2020.9059534


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