Please use this identifier to cite or link to this item: https://doi.org/10.1007/s11265-009-0430-8
Title: QRS detection based on morphological filter and energy envelope for applications in body sensor networks
Authors: Zhang, F. 
Lian, Y. 
Keywords: Body sensor networks
Electrocardiogram
Envelope
Mathematical morphology
Morphological filter
QRS detection
Wavelet transform
Wearable ECG device
Issue Date: Aug-2011
Source: Zhang, F., Lian, Y. (2011-08). QRS detection based on morphological filter and energy envelope for applications in body sensor networks. Journal of Signal Processing Systems 64 (2) : 187-194. ScholarBank@NUS Repository. https://doi.org/10.1007/s11265-009-0430-8
Abstract: Emerging body sensor networks (BSN) provide solutions for continuous health monitoring at anytime and from anywhere. The implementation of these monitoring solutions requires wearable sensor devices and thus creates new technology challenges in both software and hardware. This paper presents a QRS detection method for wearable Electrocardiogram (ECG) sensor in body sensor networks. The success of proposed method is based on the combination of two computationally efficient procedures, i.e., single-scale mathematical morphological (MM) filter and approximated envelope. The MM filter removes baseline wandering, impulsive noise and the offset of DC component while the approximated envelope enhances the QRS complexes. The performance of the algorithm is verified with standard MIT-BIH arrhythmia database as well as exercise ECG data. It achieves a low detection error rate of 0.42% based on the MIT-BIH database. © 2009 Springer Science + Business Media, LLC.
Source Title: Journal of Signal Processing Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/57163
ISSN: 19398018
DOI: 10.1007/s11265-009-0430-8
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