Multivariate approach to QRS detection

Authors

Alan B. Bond, University of Nebraska–Lincoln
Edward Carl Greco, Arkansas Tech UniversityFollow
Richard Bowser, University of Nebraska–Lincoln
Nazih N. Kadri, University of Nebraska–Lincoln
Michael H. Sketch, University of Nebraska–Lincoln

Document Type

Conference Proceeding

Publication Date

12-1-1993

Department

Electrical Engineering

Abstract

We have developed a QRS detection algorithm based on a multivariate model, in which three independent, normalized measures -- amplitude, first difference, and spatial frequency -- are combined in a weighted sum to generate an indicator variable that is then compared to a detection threshold. To increase sensitivity, we first applied and FIR, band-pass filter consisting of a cascaded series of running medians and means. The techniques appears to be exceedingly robust, correctly detecting even aberrant QRS complexes in noise-corrupted ECGs.

First Page

675

Last Page

676

Publication Title

Proceedings of the Annual Conference on Engineering in Medicine and Biology

ISBN

0780313771

Comments

At the time of publication, Edward Carl Greco was affiliated with University of Nebraska–Lincoln.

Recommended Citation

Bond, A. B., Greco, E. C., Bowser, R., Kadri, N. N., & Sketch, M. H. (1993). Multivariate approach to QRS detection. In Proceedings of the Annual Conference on Engineering in Medicine and Biology 15 (pt. 2): 675-676.