A Method for Pulse Signal Denoising Based on VMD Parameter Optimization and Grey Wolf Optimizer

Aiming at the difficulty of parameter determination when using variational modal decomposition algorithm (VMD) to decompose photoplethysmographic(PPG) pulse wave signals, α VMD parameter optimization method based on Grey Wolf Optimizer (GWO) is proposed. In this paper, the envelope entropy of the K eigenmode component (IMF) after VMD decomposition is used as the fitness function, and the grey wolf optimization algorithm (GWO) is used to find the K sum corresponding to the minimum envelope entropy of the eigenmode component α, to determine the optimal value of the VMD algorithm parameters, and then use the parameter optimized VMD algorithm to filter out the noise in the PPG signal. The experimental results show that after decomposing the PPG signal using the algorithm in this paper, the effective component and the noise component of the signal are well separated. After selecting the appropriate IMF component for reconstruction, the noise in the PPG signal is effectively filtered out.