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Innovations

Separation of EEG and ECG components based on wavelet shrinkage and variable cosine window

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Pages 135-143 | Received 25 Oct 2011, Accepted 29 Nov 2011, Published online: 23 Jan 2012
 

Abstract

During ambulatory monitoring, it is sometimes required to record an electroencephalogram (EEG) and an electrocardiogram (ECG) simultaneously. It would be ideal if both EEG and ECG could be obtained with one measurement. Here, we introduce an algorithm that combines the wavelet shrinkage and variable cosine window operation to separate the EEG and ECG components from an EEG signal recorded with a noncephalic reference (NCR). Evaluation using simulated data and actual measured data showed that accurate frequency analysis of EEG and an R-R detection-based heart rate analysis were feasible with our proposed algorithm, which improved the signal-averaging based algorithm so that ECG components containing ectopic beats can be applied.

Declaration of interest: Authors declare no conflicts of interest.

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