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Classification of Neuromuscular Junction and Tendon Recordings of Neuromuscular Diseases by Their Spectrogram

dc.contributor.authorGoker, Imran
dc.contributor.authorBaslo, Baris
dc.contributor.authorOsman, Onur
dc.contributor.authorArtug, Tugrul
dc.date.accessioned2021-03-03T12:08:16Z
dc.date.available2021-03-03T12:08:16Z
dc.identifier.citationArtug T., Goker I., Osman O., Baslo B., "Classification of Neuromuscular Junction and Tendon Recordings of Neuromuscular Diseases by Their Spectrogram", Scientific Meeting on Electric Electronics, Computer Science, Biomedical Engineerings (EBBT), İstanbul, Türkiye, 20 - 21 Nisan 2017
dc.identifier.othervv_1032021
dc.identifier.otherav_2c220c76-c1f9-48fc-90b1-2222514fd097
dc.identifier.urihttp://hdl.handle.net/20.500.12627/34391
dc.identifier.urihttps://doi.org/10.1109/ebbt.2017.7956768
dc.description.abstractIn this study, the effect of spectrograms from neuromuscular junction and tendon records for normal, neurogenic and myopathic motor units being constructed via EMG Simulator v3.6 on the differential diagnosis were investigated. Multi-layer perceptron is chosen as classifier. If only the neuromuscular junction records are applied to the network, the performance is 73.33%. If only tendon records are applied to the input of network, the performance is 94.67%. When neuromuscular junction and tendon records are applied together to the network, the performance is 100%.
dc.language.isoeng
dc.subjectBiyomedikal Mühendisliği
dc.subjectMühendislik ve Teknoloji
dc.subjectBilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği
dc.subjectSinyal İşleme
dc.subjectMÜHENDİSLİK, ELEKTRİK VE ELEKTRONİK
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectMühendislik
dc.subjectMÜHENDİSLİK, BİYOMEDİKSEL
dc.titleClassification of Neuromuscular Junction and Tendon Recordings of Neuromuscular Diseases by Their Spectrogram
dc.typeBildiri
dc.contributor.departmentİstanbul Arel Üniversitesi , ,
dc.contributor.firstauthorID65389


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