基于调Q小波变换的心电信号特征量提取方法

Extraction Method Based on Q Wavelet Transform of ECG Signal Characteristic

与传统的基于频域划分信号分解方法不同,提出了一种基于品质因数的自适应信号分解方法。利用调Q小波变换自适应生成品质因数不同的小波函数作为信号分解的基函数,利用Mallat塔式算法将复合信号分解为具有持续振荡特性的高共振分量和具有瞬态冲击特性的低共振分量,并将其用于心电信号的特征量提取。相比于小波分析、经验模态分解等方法,该方法可以有效地去除信号中的噪声及干扰,分离频谱混叠且振荡形式不同的信号。通过数值仿真和实例分析证明了该算法的优越性。

Compared with the traditional frequency domain based on the signal decomposition method,this paper proposed a adaptive signal decomposition method based on the quality factor.Using the Q-tunable wavelet transform to adaptive generate wavelet functions with different quality factor as basis functions of signal decomposition,we decomposed the compound signal into the high resonance component with sustained oscillation properties and low resonant component with transient impact properties with Mallat algorithm and used it to extract the ecg signal characteristic.This method can remove the noise and interference of the signal effectively and separate the spectrum aliasing and different oscillation signals compared with wavelet analysis and empirical mode decomposition method and so on.The results prove the superiority of the algorithm by numerical simulation and example analysis.