Wavelet-Based Denoising and Beat Detection of ECG Signal

被引：17

作者：

Faezipour, Miad ^{[1
]}

Tiwari, Tarun M. ^{[1
]}

Saeed, Adnan ^{[1
]}

Nourani, Mehrdad ^{[1
]}

Tamil, Lakshman S. ^{[1
]}

机构：

[1] Univ Texas Dallas, Qual Life Technol Lab, Richardson, TX 75083 USA

来源：

2009 IEEE/NIH LIFE SCIENCE SYSTEMS AND APPLICATIONS WORKSHOP | 2009年

关键词：

ECG feature extraction; wavelet denoising; LabVIEW;

D O I：

10.1109/LISSA.2009.4906719

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This paper presents the design and implementation of an automatic ECG beat detection system. We proposed modifications to the existing Pan-Tompkins algorithm by introducing only one set of adaptive threshold computations to reduce the amount of data processing significantly. LabVIEW signal processing tools were used to test the performance of wavelet based analysis for denoising and feature extraction of the ECG signal. Our design achieved an overall accuracy of 99.51% when applied on the MTT/BIH Arrhythmia Database, which is far better than the old method of digital filtering.

引用

页码：100 / 103

页数：4

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