Automatic Removal of Ocular Artefacts in EEG Signal by Using Independent Component Analysis and Artificial Neural Network

Küçük Resim Yok

Tarih

2017

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

IEEE

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

Ocular artefacts caused by eye movements can distort Electroencephalogram (EEG) recordings. It is important to obtain clean EEG signals in diagnosing and interpreting diseases. Meaningful EEG signals should not be distorted during the removal of artefacts. In this study, Independent Component Analysis and Artificial Neural Network were used together to remove ocular artefacts. The method was tested by using the real dataset. The Relative Error (RE) and Correlation Coefficient (CC) was used to test the performance of the method. Relative error = 0.227 0.229 and correlation coefficient = 0.941 0.088 was calculated in the performance analysis. According to the results, the proposed method is successful in removing ocular artefacts in EEG signals.

Açıklama

Medical Technologies National Congress (TIPTEKNO) -- OCT 12-14, 2017 -- TRABZON, TURKEY

Anahtar Kelimeler

ICA, removal of arefacts, artificial neural network, kurtosis

Kaynak

2017 Medical Technologies National Congress (Tiptekno)

WoS Q Değeri

N/A

Scopus Q Değeri

Cilt

Sayı

Künye