Title
A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising.
Abstract
In this paper, a simple moving average-based computing method for real-time QRS detection is proposed. In addition, for signal preprocessing our detection algorithm also incorporates a wavelet-based denoising procedure to effectively reduce the noise level for electrocardiogram (ECG) data. The overall computational structure of the proposed algorithm allows the QRS detection to be performed and implemented in real-time with high time- and memory-efficiency. Algorithm performance was evaluated against the MIT-BIH Arrhythmia Database. The numerical results indicated that the novel algorithm finally achieved about 99.5% of the detection rate for the standard database, and also, it could function reliably even under the condition of poor signal quality in the measured ECG data.
Year
DOI
Venue
2006
10.1016/j.cmpb.2005.11.012
Computer Methods and Programs in Biomedicine
Keywords
Field
DocType
Electrocardiogram (ECG),Moving average,QRS detection,Wavelet denoising
Noise reduction,Pattern recognition,Signal quality,Computer science,Noise level,Preprocessor,QRS complex,Artificial intelligence,Moving average,Wavelet denoising,Wavelet
Journal
Volume
Issue
ISSN
82
3
0169-2607
Citations 
PageRank 
References 
59
8.65
5
Authors
3
Name
Order
Citations
PageRank
Szi-Wen Chen111726.84
Hsiao-Chen Chen2659.78
Hsiao-Lung Chan317619.98