title: Application of filtering methods for removal of resuscitation artifacts from human ECG signals.
abstract: Band-pass, Kalman, and adaptive filters are used for removal of resuscitation artifacts from human ECG signals. A database of separately recorded human ECG and animal resuscitation artifact signals is used for evaluation of the methods. The considered performance criterion is the signal-to-noise ratio (SNR) improvement, defined as the ratio of the SNRs of the filtered signal and the given ECG signal. The empirical results show that for low SNR of the given signal, a band-pass filter yields the best performance, while for high SNR, an adaptive filter yields the best performance.
authors.affiliation: School of Electronics and Computer Science, University of Southampton, SO17 1BJ, UK. im@ecs.soton.ac.uk
authors.forename: Ivan
authors.initials: I
authors.lastname: Markovsky
authors.forename: Anton
authors.initials: A
authors.lastname: Amann
authors.forename: Sabine
authors.initials: S
authors.lastname: Van Huffel
mesh_terms: D000465:Algorithms; D000818:Animals; D016477:Artifacts; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D015203:Reproducibility of Results; D012151:Resuscitation; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013552:Swine; D014693:Ventricular Fibrillation / Q000175:diagnosis*