Automatic Removal of Ocular Artefacts In EEG Signal by Using Independent Component Analysis and Chauvenet Criterion
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Eye movements (saccade, blink and cause artefacts in Electroencephalogram recordings. The ocular artefact can distort the EEG signals. Removal of ocular artefact is important issue in EEG signal analysis. The main task of artefact removal algorithms is to obtain cleaned EEG without losing meaningful EEG signal. The main focus of this work is to remove ocular artefact automatically by using Independent Component Analysis and Chauvenet criterion. The method is tested on real dataset. Relative error and Correlation coefficient are used for the performance test. The performance of the proposed method was Relative error= 0.273 +/- 0.148, Correlation coefficient= 0.943 +/- 0.042 in the dataset. The results show that the porposed method effectively removes ocular artefacts in EEG.
Açıklama
Medical Technologies National Conference (TIPTEKNO) -- OCT 27-29, 2016 -- Antalya, TURKEY
Anahtar Kelimeler
ICA, removal of arefacts, Chauvenet criterion
Kaynak
2016 Medical Technologies National Conference (Tiptekno)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
