Department of Electronic Engineering, Yeungnam University, Gyeongsan, Gyeongbuk 38541, Korea.
Sensors (Basel). 2021 Mar 6;21(5):1851. doi: 10.3390/s21051851.
The aim of this paper is to find the optimal mother wavelet function and wavelet decomposition level when denoising the Doppler cardiogram (DCG), the heart signal obtained by the Doppler radar sensor system. To select the best suited mother wavelet function and wavelet decomposition level, this paper presents the quantitative analysis results. Both the optimal mother wavelet and decomposition level are selected by evaluating signal-to-noise-ratio (SNR) efficiency of the denoised signals obtained by using the wavelet thresholding method. A total of 115 potential functions from six wavelet families were examined for the selection of the optimal mother wavelet function and 10 levels (1 to 10) were evaluated for the choice of the best decomposition level. According to the experimental results, the most efficient selections of the mother wavelet function are "db9" and "sym9" from Daubechies and Symlets families, and the most suitable decomposition level for the used signal is seven. As the evaluation criterion in this study rates the efficiency of the denoising process, it was found that a mother wavelet function longer than 22 is excessive. The experiment also revealed that the decomposition level can be predictable based on the frequency features of the DCG signal. The proposed selection of the mother wavelet function and the decomposition level could reduce noise effectively so as to improve the quality of the DCG signal in information field.
本文旨在为经多普勒雷达传感器系统获取的心脏信号——多普勒心音图（DCG）的去噪过程，找到最优母小波函数和小波分解层数。为选择最适合的母小波函数和小波分解层数，本文给出了定量分析结果。通过使用小波阈值法对去噪信号的信噪比（SNR）效率进行评估，选择最优母小波和分解层数。从六个小波族中总共检查了 115 个潜在函数，以选择最优母小波函数，评估了 10 个（1 到 10）分解水平以选择最佳分解水平。根据实验结果，从 Daubechies 和 Symlets 族中选择的最优母小波函数是“db9”和“sym9”，对于所用信号最合适的分解层数是 7。由于本研究中的评价标准是去噪过程的效率，因此发现超过 22 的母小波函数是过度的。实验还表明，根据 DCG 信号的频率特征，可以预测分解层数。本文提出的母小波函数和分解层数的选择可以有效降低噪声，从而提高 DCG 信号在信息领域的质量。
