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Article: Electromyographic Analysis of Paraspinal Muscles of Scoliosis Patients Using Machine Learning Approaches

TitleElectromyographic Analysis of Paraspinal Muscles of Scoliosis Patients Using Machine Learning Approaches
Authors
Liang, RXYip, JFAN, YCheung, JPYTo, MKT
Issue Date2022
Citation
International Journal of Environmental Research and Public Health, 2022, v. 19, p. 1177 How to Cite?
DOI: http://dx.doi.org/10.3390/ijerph19031177
Persistent Identifierhttp://hdl.handle.net/10722/311318
ISI Accession Number ID
WOS:000756298100001

 

DC FieldValueLanguage
dc.contributor.authorLiang, RX-
dc.contributor.authorYip, J-
dc.contributor.authorFAN, Y-
dc.contributor.authorCheung, JPY-
dc.contributor.authorTo, MKT-
dc.date.accessioned2022-03-21T08:47:59Z-
dc.date.available2022-03-21T08:47:59Z-
dc.date.issued2022-
dc.identifier.citationInternational Journal of Environmental Research and Public Health, 2022, v. 19, p. 1177-
dc.identifier.urihttp://hdl.handle.net/10722/311318-
dc.languageeng-
dc.relation.ispartofInternational Journal of Environmental Research and Public Health-
dc.titleElectromyographic Analysis of Paraspinal Muscles of Scoliosis Patients Using Machine Learning Approaches-
dc.typeArticle-
dc.identifier.emailCheung, JPY: cheungjp@hku.hk-
dc.identifier.emailTo, MKT: mikektto@hku.hk-
dc.identifier.authorityCheung, JPY=rp01685-
dc.identifier.authorityTo, MKT=rp00302-
dc.identifier.doi10.3390/ijerph19031177-
dc.identifier.hkuros332164-
dc.identifier.volume19-
dc.identifier.spage1177-
dc.identifier.epage1177-
dc.identifier.isiWOS:000756298100001-

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