An automatic analysis method for detecting and eliminating ECG artifacts in EEG
Computers in Biology and Medicine
Hyper-trim shrinkage for denoising of ECG signal
Digital Signal Processing
De-noising by soft-thresholding
IEEE Transactions on Information Theory
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During ambulatory monitoring, it is often required to record the electroencephalogram (EEG) and the electrocardiogram (ECG) simultaneously. It would be ideal if both EEG and ECG can be obtained with one measurement. We introduce an algorithm combining the wavelet shrinkage and signal averaging techniques to extract the EEG and ECG components from an EEG lead signal to a noncephalic reference (NCR). The evaluation using simulation data and measured data showed that the normalized power spectrum unvaried in all frequency bands for the EEG components, and the sensitivity and specificity of R-wave detection for the ECG component were nearly 100%.