Robust ECG artifact removal from EEG using continuous wavelet transformation and linear regression

EEG signals are often contaminated by the ECG signal. The previous proposed methods are mostly ensemble average subtraction and ICA based. This paper proposes a robust method for detecting R peaks. Using Continuous Wavelet Transformation (CWT), the energy frequency distribution of the QRS waves in the ECG signal are exploited along with the quasi periodic nature of the R-peaks. Upon estimating the QRS data model from the ECG, the linear regression technique is applied to remove the ECG artifacts from the synchronous EEG. Result for R-peak detection is compared against a published paper, shows a better performance.