Sun Yan, Chan Kap Luk, Krishnan Shankar Muthu
Bioinformatics Institute, 138671, Singapore.
BMC Cardiovasc Disord. 2005 Sep 20;5:28. doi: 10.1186/1471-2261-5-28.
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).
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.
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.
The developed MMD method exhibits good potentials for automated ECG signal analysis and cardiovascular arrhythmia recognition.
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。
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。
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。
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。