title: Separation of electrocardiographic and encephalographic components based on signal averaging and wavelet shrinkage techniques.
abstract: 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%.
authors.affiliation: Graduate Department of Computer and Information Systems, University of Aizu, Aizu-Wakamatsu, Fukushima, Japan.
authors.forename: Motoki
authors.initials: M
authors.lastname: Sakai
authors.forename: Daming
authors.initials: D
authors.lastname: Wei
mesh_terms: D000465:Algorithms; D004562:Electrocardiography / Q000706:statistics & numerical data*; D004569:Electroencephalography / Q000706:statistics & numerical data*; D006801:Humans; D018670:Monitoring, Ambulatory / Q000706:statistics & numerical data; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted