Multi-Class Motor Imagery Classification
عنوان مقاله: Multi-Class Motor Imagery Classification
شناسه ملی مقاله: ISCEE20_002
منتشر شده در بیستمین کنفرانس ملی دانشجویی مهندسی برق ایران در سال 1400
شناسه ملی مقاله: ISCEE20_002
منتشر شده در بیستمین کنفرانس ملی دانشجویی مهندسی برق ایران در سال 1400
مشخصات نویسندگان مقاله:
M Jyannasab - Elec. Eng. Dept., Shahed University
S Seyedtabaii - Elec. Eng. Dept., Shahed University
خلاصه مقاله:
M Jyannasab - Elec. Eng. Dept., Shahed University
S Seyedtabaii - Elec. Eng. Dept., Shahed University
The Motor Imagery (MI) classification task is a high dimensionmultivariate and complicated subject. In this respect, the originalsignals are analyzed and minimal unique features of the classes areextracted to facilitate accurate classification of the actions performed.The fusion of common spatial pattern, Fisher discrimination ratio, andfilter bank alongside the SVM and CNN-LSTM are incorporated toprovide accurate clustering. As a result and after extensive simulations,it is shown that the CSP+ FDR + CNN-LSTM setup more accuratelydifferentiates the classes.
کلمات کلیدی: Motor Imagery Classification, SVM, LSTM, CSP
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1277865/