基于改进三维卷积网络的非接触式生理参数检测方法  

Non-contact physiological parameter detection method based on improved three-dimensional convolution network

作　　者：徐展宇 陈兆学[1] XU Zhanyu;CHEN Zhaoxue(School of Health Science and Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学健康科学与工程学院,上海200093

出　　处：《中国医学物理学杂志》2025年第4期479-488,共10页Chinese Journal of Medical Physics

基　　金：国家中医药管理局中医药创新团队及人才支持计划(ZYYCXTD-D-202208)。

摘　　要：远程光电容积描记法(rPPG)是从面部视频中测量心率等生理参数的方法,针对现有的心率测量方法难以同时兼顾高准确率和轻量化的问题,提出一种改进的三维卷积网络模型实现基于面部视频的非接触式生理参数检测。在预处理时,使用YuNet模型替代传统人脸检测器,从而快速且精确地识别人脸区域。此外,将注意力机制和残差模块嵌入到三维卷积网络中提取通道和空间的关键特征,并使用长短期记忆网络作为时期记忆模块捕捉数据中的长期依赖关系。实验结果表明,所提出Res-CHATM模型在公开数据集UBFC-rPPG和PURE进行心率评估交叉实验时分别取得MAE=2.19 BPM,RMSE=7.02 BPM,C=0.95以及MAE=1.65 BPM,RMSE=3.44 BPM,C=0.98的优异效果,进一步验证了模型预测值与真实值之间的一致性以及融合模块的有效性,展示了高效轻量化模型在rPPG技术中的潜力。Remote photoplethysmography is a method of measuring physiological parameters such as heart rate from facial video.For overcoming the difficulties in achieving both high accuracy and lightweight by the existing heart rate measurement methods,an improved three-dimensional convolution network model is proposed to realize non-contact physiological parameter detection in facial video.In the pre-processing,YuNet model takes place of the traditional face detector,so that the face region can be recognized quickly and accurately.In addition,attention mechanisms and residual modules are embed into three-dimensional convolution network to extract key channel and spatial features,with long short-term memory networks used as period memory modules to capture long-term dependencies in the data.The experimental results show that the proposed Res-CHATM model achieves excellent results of MAE=2.19 BPM,RMSE=7.02 BPM,C=0.95,and MAE=1.65 BPM,RMSE=3.44 BPM,C=0.98 in the cross experiments on public datasets UBFC-rPPG and PURE for heart rate estimation.The consistency between the predicted value and the real value and the effectiveness of the fusion module are further verified,demonstrating the potential of efficient lightweight model in remote photoplethysmography.

关 键 词：非接触式 心率检测 混合注意力机制 信号处理 

分 类 号：R318[医药卫生—生物医学工程] TP391[医药卫生—基础医学]