基于鲸鱼优化算法的VMD-NLM脉搏信号滤波算法研究

针对采集到的脉搏波信号中存在基线漂移和高频噪声等干扰，导致后续病理研究分析困难、测量精度相对较差的问题，提出了一种改进的变分模态分解和非局部均值降噪结合的滤波算法。针对变分模态参数选取不同对结果存在不同影响的问题，采取鲸鱼优化算法自适应选取合适的参数，并根据排列熵结果筛选模态分量，对噪声分量进行非局部均值滤波，最后将信号重构，实现对脉搏波信号的噪声去除。实验结果表明：含噪信号经过改善后的滤波算法处理后，其信噪比与均方根误差均优于其他降噪方法，证明该算法能够有效地滤除信号的噪声，有助于脉搏波的分析处理。

VMD-NLM pulse signal filtering algorithm based on whale optimization algorithm

To solve the problem that the collected pulse wave signal is easily disturbed by high frequency noise and baseline drift, which make subsequent pathological research and analysis difficult and the measurement accuracy of inferior quality, an improved filtering algorithm combining variational mode decomposition and non-local mean noise reduction was proposed. Aiming at the problem that the selection of variational modal parameters has different effects on the results, the whale optimization algorithm was used to adaptively select appropriate parameters, and the modal components were screened according to the permutation entropy results. The experimental results show that the signal-to-noise ratio and root mean square error of the improved signal are better than other noise reduction methods after being processed by the filtering algorithm.