title: Event-synchronous cancellation of the heart interference in biomedical signals.
abstract: A two-pass adaptive filtering algorithm is proposed for cancellation of recurrent interferences such as the heart interference in biomedical signals. In the first pass, an average waveform in one period of the interference is estimated by event-synchronous (QRS-synchronous) averaging of the corrupted signal. In a second pass, an adaptive Schur recursive least squares (RLS) lattice filter is used to cancel the interference by using the event synchronously repeated estimated average waveform of the interference as an artificial reference signal. One key feature of this approach is that the ECG is only used for QRS synchronization and not directly as a reference signal for adaptive filtering. Thus the proposed algorithm can be applied to interference problems where ECG and true interference are almost synchronous but show considerably different waveforms. This is usually the case with the heart interference in biomedical signals. Both off-line and real-time implementations of the event synchronous interference canceller are described. The method is applied to the cancellation of the heart interference in magnetoencephalogram (MEG) signals and to the effective isolation of ventricular extrasystoles (VES) in magnetocardiogram (MCG) signals. Experimental results are shown. The new method typically attenuates the amplitudes of R-wave and T-wave interference components by an amplitude factor of 30 without influencing the MEG events of interest.
authors.affiliation: Fachhochschule Furtwangen, Germany.
authors.forename: P
authors.initials: P
authors.lastname: Strobach
authors.forename: K
authors.initials: K
authors.lastname: Abraham-Fuchs
authors.forename: W
authors.initials: W
authors.lastname: Härer
mesh_terms: D000465:Algorithms; D016477:Artifacts; D004562:Electrocardiography; D006801:Humans; D016018:Least-Squares Analysis; D015225:Magnetoencephalography; D008955:Models, Cardiovascular; D012815:Signal Processing, Computer-Assisted