For the problem of poor initial filtering effect of normalized least mean square (NLMS) algorithm and poor robustness of non-local means (NLM) filtering, this paper proposed an improved model based on variational modal decomposition (VMD)-Hausdorff distance non-local means (HDNLM) filtering. For the power line interferenceand white Gaussian noise in lower extremity the EMG signal, VMD was used to decompose the noisy signal, HDNLM was used to filter the decomposed signal, and the filtered output signal was superimposed, finally, the performance of the algorithm was evaluated by signal-to-noise ratio (SNR) and improved root mean square error (IRMSE).The experimental results show that the NLM and its improved NLM (INLM) are better filtered on average compared to VMD-HDNLM and NLMS when the noise amplitude is 0.1~0.2 M in 16 muscle EMG signals,but when the EMG noise amplitude was 0.3~0.5 M, the IRMSE values of VMD-HDNLM increased by 0.64%, 1.84%, 3.11% and 13.95%, 12.77, 11.07% and 1.05%, 1.74%, 2.85% on average relative to NLM, NLMS and INLM.At the same time, the VMD-HDNLM algorithm has a wider range of parameters than the NLM and INLM algorithms to obtain a smaller value of IRMSE, its robustness is better, and the probability of obtaining a better value in actual situations is greater.