Automatic removal of ocular artefacts in EEG signal by using independent component analysis and artificial neural network
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
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. © 2017 IEEE.
Açıklama
2017 Medical Technologies National Conference, TIPTEKNO 2017 -- 12 October 2017 through 14 October 2017 -- -- 134046
Anahtar Kelimeler
Artificial neural network, Ica, Kurtosis, Removal of arefacts
Kaynak
2017 Medical Technologies National Conference, TIPTEKNO 2017
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
2017-January
