Literature DB >> 7851927

Detection of ECG characteristic points using wavelet transforms.

C Li1, C Zheng, C Tai.   

Abstract

An algorithm based on wavelet transforms (WT's) has been developed for detecting ECG characteristic points. With the multiscale feature of WT's, the QRS complex can be distinguished from high P or T waves, noise, baseline drift, and artifacts. The relation between the characteristic points of ECG signal and those of modulus maximum pairs of its WT's is illustrated. By using this method, the detection rate of QRS complexes is above 99.8% for the MIT/BIH database and the P and T waves can also be detected, even with serious baseline drift and noise.

Mesh:

Year:  1995        PMID: 7851927     DOI: 10.1109/10.362922

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  71 in total

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8.  Wavelet-based analysis of heart-rate-dependent ECG features.

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9.  Unconstrained detection of respiration rhythm and pulse rate with one under-pillow sensor during sleep.

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10.  A wavelet transform based feature extraction and classification of cardiac disorder.

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Journal:  J Med Syst       Date:  2014-07-15       Impact factor: 4.460

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