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基于形态变换的心电图信号特征波检测

Characteristic wave detection in ECG signal using morphological transform.

作者信息

Sun Yan, Chan Kap Luk, Krishnan Shankar Muthu

机构信息

Bioinformatics Institute, 138671, Singapore.

出版信息

BMC Cardiovasc Disord. 2005 Sep 20;5:28. doi: 10.1186/1471-2261-5-28.

Abstract

BACKGROUND

Detection of characteristic waves, such as QRS complex, P wave and T wave, is one of the essential tasks in the cardiovascular arrhythmia recognition from Electrocardiogram (ECG).

METHODS

A multiscale morphological derivative (MMD) transform-based singularity detector, is developed for the detection of fiducial points in ECG signal, where these points are related to the characteristic waves such as the QRS complex, P wave and T wave. The MMD detector is constructed by substituting the conventional derivative with a multiscale morphological derivative.

RESULTS

We demonstrated through experiments that the Q wave, R peak, S wave, the onsets and offsets of the P wave and T wave could be reliably detected in the multiscale space by the MMD detector. Compared with the results obtained via with wavelet transform-based and adaptive thresholding-based techniques, an overall better performance by the MMD method was observed.

CONCLUSION

The developed MMD method exhibits good potentials for automated ECG signal analysis and cardiovascular arrhythmia recognition.

摘要

背景

检测特征波,如QRS波群、P波和T波,是心电图(ECG)中心血管心律失常识别的基本任务之一。

方法

开发了一种基于多尺度形态学导数(MMD)变换的奇异点检测器,用于检测ECG信号中的基准点,这些点与QRS波群、P波和T波等特征波相关。MMD检测器通过用多尺度形态学导数代替传统导数来构建。

结果

我们通过实验证明,MMD检测器可以在多尺度空间中可靠地检测到Q波、R峰、S波、P波和T波的起始点和终点。与基于小波变换和自适应阈值技术获得的结果相比,MMD方法的整体性能更好。

结论

所开发的MMD方法在自动ECG信号分析和心血管心律失常识别方面具有良好的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/862f/1266028/37d34e1f0009/1471-2261-5-28-1.jpg

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