Separation of EOG artifacts from EEG signals using Hilbert-Huang transform - Details

Author：

Li, Ming-Ai (Li, Ming-Ai.) (Scholars：李明爱) | Yang, Lin-Bao (Yang, Lin-Bao.) | Yang, Jin-Fu (Yang, Jin-Fu.) (Scholars：杨金福)

Indexed by：

EI Scopus

Abstract：

The　electroencephalogram　(EEG)　signal　is　highly　weak　and　usually　contaminated　by　electrooculogram　(EOG),　this　presents　serious　problems　for　EEG　data　interpretation　and　analysis.　So,　the　automatic　removal　of　EOG　artifacts　from　EEG　has　been　an　important　problem.　In　this　paper,　Hilbert-Huang　transform　(HHT)　is　applied　to　remove　the　EOG　artifacts　arising　from　eye　movement.　According　to　the　local　time-frequency　properties　of　EOG　and　the　statistic　characteristics　of　intrinsic　mode　function　(IMF)　of　raw　EEG,　the　EOG　contamination　can　be　eliminated　from　EEG　after　threshold　filter　of　IMF.　The　proposed　method　is　fit　for　the　non-stationary　signal　because　of　the　highly　perfect　local　time-frequency　properties　of　HHT.　The　experiment　results　show　that　it　is　very　efficient　at　automatically　subtracting　the　eye　movement　artifacts.　©　2011　IEEE.

Keyword：

Signal processing Eye movements Mathematical transformations Electroencephalography

Author Community：

[ 1 ] [Li, Ming-Ai]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
[ 2 ] [Yang, Lin-Bao]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
[ 3 ] [Yang, Jin-Fu]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China