Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/12100
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dc.contributor.authorPattamaset S.
dc.contributor.authorCharoenpong T.
dc.contributor.authorCharoensiriwath S.
dc.date.accessioned2021-04-05T03:01:55Z-
dc.date.available2021-04-05T03:01:55Z-
dc.date.issued2020
dc.identifier.other2-s2.0-85084033564
dc.identifier.urihttps://ir.swu.ac.th/jspui/handle/123456789/12100-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85084033564&doi=10.1109%2fKST48564.2020.9059534&partnerID=40&md5=aab02472f38bf05e44734d9711ac300a
dc.description.abstractThis 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.subjectPatient treatment
dc.subjectSports
dc.subjectAutomatic systems
dc.subjectHistogram analysis
dc.subjectImage processing technique
dc.subjectKnee osteoarthritis
dc.subjectOsteoarthritis of the knee
dc.subjectOverall accuracies
dc.subjectPhysical exercise
dc.subjectSkeletonization
dc.subjectImage processing
dc.titleEvaluation of physical exercise for osteoarthritis of the knee through image processing technique
dc.typeConference Paper
dc.rights.holderScopus
dc.identifier.bibliograpycitationKST 2020 - 2020 12th International Conference on Knowledge and Smart Technology. (2020), p.127-130
dc.identifier.doi10.1109/KST48564.2020.9059534
Appears in Collections:Scopus 1983-2021

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