İki kanal yüzey EMG işareti ile el aç/kapa ve el parmaklarının sınıflandırılması
| Autor: | Ramazan Tekin, Necmettin Sezgin, Ömer Faruk Ertuğrul, Mehmet Emin Tagluk |
|---|---|
| Přispěvatelé: | Batman Üniversitesi Mühendislik - Mimarlık Fakültesi Elektrik-Elektronik Mühendisliği Bölümü, Batman Üniversitesi Mühendislik - Mimarlık Fakültesi Bilgisayar Mühendisliği Bölümü |
| Jazyk: | turečtina |
| Rok vydání: | 2017 |
| Předmět: |
medicine.diagnostic_test
Channel (digital image) Computer science business.industry Speech recognition İkiz Spektrum Analizi Electromyography Thumb Surface Electromyogram Signal Aşırı Öğrenme Makineleri Bispectrum Analysis body regions medicine.anatomical_structure Forearm medicine Computer vision Artificial intelligence Closing (morphology) business Extreme Learning Machine Bispectrum Extreme learning machine Yüzey Elektromiyogramı |
| Popis: | In this study, two-channel surface electromyogram (sEMG) signals were used to classify hand open/close with fingers. The bispectrum analysis of the sEMG signal recorded with surface electrodes near the region of the muscle bundles on the front and back of the forearm was classified by extreme learning machines (ELM) based on phase matches in the EMG signal. EMG signals belonging to 17 persons, 8 males and 9 females, with an average age of 24 were used in the study. The fingers were classified using ELM algorithm with 94.60% accuracy in average. From the information obtained through this study, it seems possible to control finger movements and hand opening/closing by using muscle activities of the forearm which we hope to lead to control of intelligent prosthesis hands with high degree of freedom. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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