Research on Heart Rate Detection Method of Face Video Based on Improved DRSN

ZHAO Ya; LYU Haoyuan; TIAN Xiaocai; LU Yao

doi:10.3969/j.issn.1672-9722.2025.11.029

Abstract：At present,the non-contact heart rate detection method based on face video has many problems,such as large noise interference,low accuracy and poor robustness.This paper proposes a heart rate detection method for face video based on im-proved DRSN,which can effectively solve the above problems.The improved DRSN network,on the one hand,modifies SENet in the original DRSN network to ECA-Net to effectively avoid the impact of SENet dimensionality reduction on the attention of learning channels,while maintaining the information sharing between channels,so that the channel attention mechanism can better serve the soft threshold function.On the other hand,it replaces the ReLU activation function in the original DRSN network with Leaky ReLU to reduce the occurrence of dead neurons caused by the ReLU activation function.The experimental results show that the MAE de-creases by 18.7%,RMSE decreases by 17.6%,SD decreases by 17.9%,and Pearson correlation coefficient r increases by 4.3%on the VIPL dataset.In PURE data set,MAE decreases by 9.5%,RMSE decreases by 15.2%,SD decreased by 10%,and Pearson cor-relation coefficient r increases by 0.3%.It has been verified that the improved face video heart rate detection method has higher de-tection accuracy and stronger anti-interference ability,effectively improving the accuracy and robustness of face video heart rate de-tection.