基于变分模态分解的脉搏信号联合去噪

Combine denoising of pulse signal based on variational modal decomposition

针对脉搏信号的特点和采集过程中出现的运动、基线漂移和工频干扰等所引起的噪声,提出基于变分模态分解(VMD)的联合去噪方法。通过计算采集的脉搏信号近似熵为评价指标迭代优化VMD参数,结合自相关函数、频谱和平滑滤波等方法,实现脉搏信号的降噪处理。仿真和实测数据实验表明,联合去噪方法效果好,在含噪信号的信噪比为5.513 1 dB时,去噪后信噪比19.581 3 dB,均方根误差为0.438 5,信噪比和均方根误差均明显优于自适应噪声集合经验模态分解(ICEEMDAN)、VMD等方法。去噪后的脉搏信号清晰完整,能够为疾病预防及健康监测提供准确的数据支持。

This paper proposes a joint denoising method based on variational mode decomposition to address the characteristics of pulse signals and the noise caused by motion,baseline drift,and power frequency interference during the acquisition process.By calculating the approximate entropy of the collected pulse signal as the evaluation index,the variational mode decomposition parameters are iteratively optimized,and methods such as autocorrelation function,spectrum,and smoothing filtering are combined to achieve denoising of the pulse signal.The simulation and real data experiments show that the joint denoising method proposed in this paper is effective.When the signal-to-noise ratio of the noisy signal is 5.513 1 dB,the signal-to-noise ratio after denoising is 19.581 3 dB,and the root-mean-square deviation is 0.438 5.The signal-to-noise ratio and root-mean-square deviation are significantly better than the adaptive noise set empirical mode decomposition(ICEEMDAN),VMD and other methods.The denoised pulse signal is clear and complete,providing accurate data support for disease prevention and health monitoring.