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dc.contributor.authorKulwanee Meedengen_US
dc.contributor.authorWarakorn Charoensuken_US
dc.contributor.authorKorakod Panichen_US
dc.contributor.authorKakanand Srungboonmeeen_US
dc.contributor.otherMahidol Universityen_US
dc.date.accessioned2018-12-11T02:50:13Z
dc.date.accessioned2019-03-14T08:01:31Z-
dc.date.available2018-12-11T02:50:13Z
dc.date.available2019-03-14T08:01:31Z-
dc.date.issued2016-01-01en_US
dc.identifier.citationIECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences. (2016), 110-114en_US
dc.identifier.other2-s2.0-85015659604en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85015659604&origin=inwarden_US
dc.identifier.urihttp://repository.li.mahidol.ac.th/dspace/handle/123456789/40636-
dc.description.abstract© 2016 IEEE. Early stage of chondromalacia patella is usually asymptomatic. Detection of chondromalacia patella sooner can delay further cartilage degeneration by appropriate exercise prescription and behavioral change. The purpose of this study is to preliminary examine asymptomatic subjects and investigate the knee vibroarthrographic (VAG) signals in order to suggest possible parameters to detect chondromalacia patella at the early stage. Frequency characteristics of the signals which include energy and the summing of spectral power in each 500 Hz frequency band were observed. Energy and spectral power of the VAG signals with chondromalacia patella were obviously higher than normal VAG signals, particularly in the high frequency bands (higher than 500 Hz). VAG signal is therefore a promising tool in detection of early stage chondromalacia patella.en_US
dc.rightsMahidol Universityen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85015659604&origin=inwarden_US
dc.subjectEngineeringen_US
dc.titleSpectral analysis of knee vibroarthrographic signals in asymptomatic chondromalacia patellaen_US
dc.typeConference Paperen_US
dc.rights.holderSCOPUSen_US
dc.identifier.doi10.1109/IECBES.2016.7843425en_US
Appears in Collections:Scopus 2016-2017

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