Title :
Multi-lead QRS detection using window pairs
Author :
Torbey, S. ; Akl, Selim G. ; Redfearn, D.P.
Author_Institution :
Queen´s Univ., Kingston, ON, Canada
fDate :
Aug. 28 2012-Sept. 1 2012
Abstract :
We designed a novel approach for multi-lead QRS detection. The algorithm uses one equation with two different window widths to generate a feature signal and a detection threshold. This enables it to adapt to various changes in QRS morphology and noise levels, resulting in a detection error rate of just 0.29% on the MIT-BIH Arrhythmia Database. The algorithm is also computationally efficient and capable of resolving differences between multiple leads by automatically attaching a confidence value to each QRS detection.
Keywords :
electrocardiography; medical signal detection; medical signal processing; MIT-BIH Arrhythmia Database; QRS morphology; confidence value; detection threshold; feature signal generation; multilead QRS detection; noise level; window pairs; window width; Databases; Detection algorithms; Electrocardiography; Feature extraction; Morphology; Noise; Rhythm; Algorithms; Arrhythmias, Cardiac; Electrocardiography; Humans; Signal Processing, Computer-Assisted;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
DOI :
10.1109/EMBC.2012.6346631