Aiming at the low accuracy of respiratory wave extraction, an improved method for respiratory wave extraction from photoplethysmography (PPG) signal is proposed. Ten groups of pulse and respiratory signals were obtained from the mimic database. The variation mode decomposition (VMD) algorithm optimized by genetic mutation particle swarm optimization is used to decompose the pulse signal of photo capacitance product in the same period, and the intrinsic mode function (IMF) is obtained. The IMF component with correlation coefficient greater than 0.3 is selected to reconstruct the respiratory signal, and the reconstructed respiratory signal is compared with the original respiratory signal. The experimental results show that the average accuracy of respiratory rate is 0.95, the average value of waveform correlation coefficient (RCC) is 0.9451, and the average value of root mean square error (RMSE) is 2.0110. Compared with EMD and EEMD, the algorithm improves respiratory rate by 5% and 3%, and RCC by 19.96% and 13.17%, with higher accuracy. At the same time, the algorithm overcomes the uncertainty of penalty factor and decomposition level selection in VMD algorithm. This is of great significance to clinical practice.