A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising

Szi Wen Chen; Hsiao Chen Chen; Hsiao Lung Chan

doi:10.1016/j.cmpb.2005.11.012

A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising

Szi Wen Chen^*, Hsiao Chen Chen, Hsiao Lung Chan

^*Corresponding author for this work

Chang Gung University

Research output: Contribution to journal › Journal Article › peer-review

232 Scopus citations

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.

Original language	English
Pages (from-to)	187-195
Number of pages	9
Journal	Computer Methods and Programs in Biomedicine
Volume	82
Issue number	3
DOIs	https://doi.org/10.1016/j.cmpb.2005.11.012
State	Published - 06 2006

Keywords

Electrocardiogram (ECG)
Moving average
QRS detection
Wavelet denoising

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10.1016/j.cmpb.2005.11.012

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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.",

keywords = "Electrocardiogram (ECG), Moving average, QRS detection, Wavelet denoising",

author = "Chen, {Szi Wen} and Chen, {Hsiao Chen} and Chan, {Hsiao Lung}",

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T1 - A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising

AU - Chen, Szi Wen

AU - Chen, Hsiao Chen

AU - Chan, Hsiao Lung

PY - 2006/6

Y1 - 2006/6

N2 - 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.

AB - 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.

KW - Electrocardiogram (ECG)

KW - Moving average

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KW - Wavelet denoising

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JO - Computer Methods and Programs in Biomedicine

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A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising

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Keywords

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