An improved performance of support vector machine to classify EEG motor imagery based on differential asymmetry

• Autorzy: Putranto Yulianto Tejo , Putra Oddy Virgantara , Hafidz Isa , Sardjono Arief , Hariadi Mochamad , Putranto Yulianto Tejo

Identyfikatory

DOI

10.15199/48.2023.06.40

Warianty tytułu

PL

Ulepszona wydajność maszyny wektorów nośnych do klasyfikacji obrazów motorycznych EEG w oparciu o asymetrię różnicową

• Języki publikacji: EN

Abstrakty

EN

One challenge in EEG motor imaging is th e low signal-to-noise ratio of brain signals. Its emergence in the accurate rendition of brain signals varies significantly from person to person. Here, we propose a framework to classify tasks based on fusion features using a Support Vector Machine. Our features are acquired from Discrete Wavelet Transform and Empirical Mode Decomposition. Subsequently, the disparity between measurements of left and right brain signals was calculated. Our proposed work significantly improves accuracy from 83.29 % to 93.16 % compared to previous work.

PL

Jednym z wyzwań w obrazowaniu motorycznym EEG jest niski stosunek sygnału do szumu sygnałów mózgowych. Jego pojawienie się w dokładnym przekazywaniu sygnałów mózgowych różni się znacznie w zależności od osoby. Tutaj proponujemy ramy do klasyfikowania zadań w oparciu o funkcje fuzji przy użyciu maszyny wektorów nośnych. Nasze funkcje są uzyskiwane z dyskretnej transformacji falkowej i dekompozycji trybu empirycznego. Następnie obliczono rozbieżność między pomiarami sygnałów lewego i prawego mózgu. Nasza proponowana praca znacznie poprawia dokładność z 83,29% do 93,16% w porównaniu z poprzednią pracą.

Słowa kluczowe

EN

EEG motor imagery; discrete wavelet transform; empirical mode decomposition; differential asymmetry

PL

EEG; dyskretna transformata falkowa; asymetria

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2023
• Tom: R. 99, nr 6
• Strony: 196--203
• Opis fizyczny: Bibliogr. 25 poz., rys., tab.

Twórcy

autor

Putranto Yulianto Tejo

• Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember
• Universitas Katolik Soegijapranata

autor

Putra Oddy Virgantara

• Department of Informatics, Universitas Darussalam Gontor

autor

Hafidz Isa

• Department of Electrical Engineering, Institut Teknologi Telkom Surabaya

autor

Sardjono Arief

• Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember

autor

Hariadi Mochamad

• Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember

autor

Putranto Yulianto Tejo

• Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember
• University Center of Excellence on Artificial Intelligence for Healthcare and Society (UCE AIHeS)

Bibliografia

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