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作 者:刘爽娜 黄德启[1] 王梦梦 LIU Shuangna;HUANG Deqi;WANG Mengmeng(School of Electrical Engineering,Xinjiang University,Urumqi 830017,China)
机构地区:[1]新疆大学电气工程学院,新疆乌鲁木齐830017
出 处:《现代电子技术》2023年第9期61-65,共5页Modern Electronics Technique
基 金:国家自然科学基金项目(51468062)。
摘 要:针对PPG信号采集过程中存在大量混合噪声的问题,提出一种变分模态分解(VMD)改进小波阈值降噪的降噪算法。首先通过傅里叶变换得到脉搏波信号频域信息,确定分解个数和主频率;然后利用变分模态分解算法将含噪声的PPG信号分解为一系列固有模态分量,分解过后确定各分量的中心频率,并筛选有效固有模态分量;最后利用改进后的小波阈值函数对残余噪声进行降噪处理,避免了软阈值的恒定偏差,又保证了阈值函数的连续性,降噪后的信号与原始信号相关系数均值为0.934 7,比变分模态分解方法重构信号提升了7.1%。与其他降噪算法相比,信噪比分别提高了5.77 dB、5.38 dB、4.5 dB,均方根误差分别降低了26.1%、16.8%、7.4%。实验结果表明,通过理论计算、数值模拟和应用研究验证了所提方法的有效性和优越性,在滤波效果和信号保真度之间取得了很好的平衡。Since there is a large amount of mixed noise in PPG signal acquisition process,a denoising algorithm of wavelet threshold denoising optimized by variational mode decomposition(VMD)is proposed.The frequency domain information of pulse wave signal is obtained by Fourier transform.The number of decomposition and the main frequency are determined.And then,the VMD algorithm is used to decompose the PPG signal with noise into a series of natural mode components.After decomposition,the central frequencies of each component are determined,and the effective natural mode components are screened.The improved wavelet threshold function is used to reduce the residual noise to avoid the constant deviation of soft threshold and ensure the continuity of threshold function.The mean correlation coefficient between the denoised signal and the original signal is 0.9347,which is 7.1%higher than that of the reconstructed signal of the VMD method.In comparison with other noise reduction algorithms,its SNR is increased by 5.77 dB,5.38 dB and 4.5 dB respectively,and its root mean square error is reduced by 26.1%,16.8%and 7.4%,respectively.The results of theoretical calculation,numerical simulation and application research have verified the effectiveness and superiority of the proposed method.A good balance between filtering effect and signal fidelity is achieved.
关 键 词:降噪算法 小波阈值函数 信号分解 变分模态分解 降噪处理 理论计算 数值模拟
分 类 号:TN29-34[电子电信—物理电子学] TP391.9[自动化与计算机技术—计算机应用技术]
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