Feature extraction and classification of neuromuscular diseases using scanning EMG

dc.contributor.author	Artuǧ, N.T.
dc.contributor.author	Göker, I.
dc.contributor.author	Bolat, B.
dc.contributor.author	Tulum, G.
dc.contributor.author	Osman, O.
dc.contributor.author	Baslo, M.B.
dc.date.accessioned	2021-12-21T08:41:45Z
dc.date.available	2021-12-21T08:41:45Z
dc.date.issued	2014
dc.identifier.isbn	9.78148E+12
dc.identifier.uri	https://doi.org/10.1109/INISTA.2014.6873628
dc.identifier.uri	http://dspace.yeniyuzyil.edu.tr:8080/xmlui/handle/20.500.12629/1510
dc.description.abstract	In this study a new dataset are prepared for neuromuscular diseases using scanning EMG method and four new features are extracted. These features are maximum amplitude, phase duration at the maximum amplitude, maximum amplitude times phase duration, and n
dc.language.iso	English
dc.publisher	IEEE Computer Society
dc.title	Feature extraction and classification of neuromuscular diseases using scanning EMG
dc.type	Conference Paper
dc.relation.journal	INISTA 2014 - IEEE International Symposium on Innovations in Intelligent Systems and Applications, Proceedings
dc.identifier.startpage	262
dc.identifier.endpage	265
dc.identifier.doi	10.1109/INISTA.2014.6873628