【摘要】 心电信号是一种非平稳并具有很多奇异点的微弱信号。小波变换中的模极大值消噪法具有非线性及自适应性,小波的这种特性对于类似于心电信号这种非平稳微弱信号是十分适用的。针对传统的消噪方法在处理心电信号时的局限性,研究了小波变换的时-频局部化特性及基于多分辨率分析的信号小波分解和重构算法———Mallat算法。采用小波分析的模极大值法实现对QRS波R峰值点的检测,以及对心电信号的消噪处理。通过试验研究可知,运用小波进行QRS波检测,QRS波的识别率高达99.9%,经过消噪重构后的心电信号信噪比较原始信号有较大提高。更多还原

【Abstract】 The electrocardiogram signal is a unstationary weak signal with a lot of distinguished vertex.The noise elimination method of the mold maximum value in the wavelet transformation has nonlinearity and the quality of self adaptation.The quality of the wavelet is very applicable to the unstationary weak signal which resembles the electrocardiogram signal.In this paper, the time to frequency localization quality of the wavelet,and the signal wavelet resolution and reconstruction algorithm Mallat which is based on the multiple resolution analysis,were studied according to the limitation of the traditional noise elimination method in the processing of the electrocardiogram signal.The detection of the R peak value of the QRS wave and the noise elimination were carried out by the method of the mold maximum value.The experiment indicates that the identification rate of the QRS wave is to be 99.9% through the detection of the wavelet.The signal-to-noise ratio of the electrocardiogram signal has been greatly improved on the primordial signal by the reconstruction of the wavelet algorithm.更多还原