dc.contributor.author | Goker, Imran | |
dc.contributor.author | Baslo, Baris | |
dc.contributor.author | Osman, Onur | |
dc.contributor.author | Artug, Tugrul | |
dc.date.accessioned | 2021-03-03T12:08:16Z | |
dc.date.available | 2021-03-03T12:08:16Z | |
dc.identifier.citation | Artug 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.other | vv_1032021 | |
dc.identifier.other | av_2c220c76-c1f9-48fc-90b1-2222514fd097 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12627/34391 | |
dc.identifier.uri | https://doi.org/10.1109/ebbt.2017.7956768 | |
dc.description.abstract | In 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.iso | eng | |
dc.subject | Biyomedikal Mühendisliği | |
dc.subject | Mühendislik ve Teknoloji | |
dc.subject | Bilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği | |
dc.subject | Sinyal İşleme | |
dc.subject | MÜHENDİSLİK, ELEKTRİK VE ELEKTRONİK | |
dc.subject | Mühendislik, Bilişim ve Teknoloji (ENG) | |
dc.subject | Mühendislik | |
dc.subject | MÜHENDİSLİK, BİYOMEDİKSEL | |
dc.title | Classification of Neuromuscular Junction and Tendon Recordings of Neuromuscular Diseases by Their Spectrogram | |
dc.type | Bildiri | |
dc.contributor.department | İstanbul Arel Üniversitesi , , | |
dc.contributor.firstauthorID | 65389 | |