基于复值小波分解的QRS波群检测算法

A Method of QRS Complexes Detection Based on Complex Wavelet Decomposing

心电信号特征参数的提取和识别是心电图分析和诊断的基础。在心电信号的分析中,QRS波群快速准确的检测非常重要,它是相关参数计算和诊断的前提。本文对心电信号进行复值小波分解后,利用分解结果的模值来检测QRS波。由于心电信号的形态和幅值因人而异,所以用自学习算法来调整阈值以适应信号的变化。用MIT-BIH心电数据库中的数据对以上方法进行验证,QRS波群的检测率高达99.81%以上。最后,在检测出QRS波群特征点的基础上,利用相类似的方法检测出P、T波。

The extraction and identification of ECG（electrocardiogram） signal characteristic parameters are the basic steps toward ECG analysis and diagnosis.The fast and precise detection of QRS complexes is very important in ECG signal analysis,for it is the precondition of the correlative parameters calculation and diagnosis.In our work,firstly,we used the modulus value of complex wavelet decomposition to detect QRS complexes from ECG signal.As the shape and amplitude of ECG signal varies from person to person,we utilized the self-learning algorithm for adjusting the threshold to adapt the changes.The correct detection rate of QRS complexes is up to 99.81% based on MIT-BIH ECG data.Finally,we used the similar methods to detect the P and T waves,after QRS complexes detection.