MP-Based Method on Detecting and Eliminating the Synchronous ECG Artifacts in the EEG Signals

A method is proposed to detect and eliminate the synchronous ECG artifacts in the EEG Signals based on the matching pursuit algorithm, which doesn't require the additional synchronous ECG channel or multichannel signals. By using the mixed over-complete dictionary, the EEG signals based on the matching pursuit algorithm are decomposed into atoms. The atoms that have the similar morphological characteristics of R-wave are selected to detect the synchronous ECG R-peak artifacts. Then, the adaptive threshold algorithm is introduced to filter the false detection induced by the morphological characteristics of both ECG artifacts and background EEG signals. At last, the elimination of detected ECG artifacts is realized by the ensemble average subtraction method. By analyzing EEG signals in MIT/BIH database, it presents the excellent result with mean error ratio $1.70\%$.