基于长期递归卷积网络的无创血压测量  

Noninvasive blood pressure measurement based on long-term recursive convolution network

作　　者：陈晓[1,2] 杨瑶[1] Chen Xiao;Yang Yao(School of Electronic and Information Engineering,Nanjing University of Information Science and Technology,Nanjing 210044,China;Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,Nanjing University of Information Science and Technology,Nanjing 210044,China)

机构地区：[1]南京信息工程大学电子与信息工程学院,南京210044 [2]南京信息工程大学大气环境与装备技术协同创新中心,南京210044

出　　处：《电子测量技术》2022年第4期139-146,共8页Electronic Measurement Technology

摘　　要：血压是能够反映人们身体健康的一个重要指标,随着高血压人群分布范围日益增大,连续血压的监测变得愈发重要。本文提出了基于长期递归卷积网络对光电容积脉搏波进行血压连续无创测量的方法。首先将利用光电容积法采集到的脉搏波信号归一化、阈值处理和特征提取,然后用长期递归卷积网络从脉搏波中计算出血压。实验表明,当光电容积脉搏波信号直接输入时,所提方法比长短期记忆网络的平均绝对误差和均方误差分别提升了56.00%和73.25%。将特征参数作为输入时,该实验比光电容积脉搏波信号直接输入时的平均绝对误差和均方误差提升了59.55%和87.41%,相比直接输入,特征参数输入的实验效果更好,实现了血压的精确测量。Blood pressure is an important indicator of people′s health.With the increasing distribution of hypertension,continuous blood pressure monitoring becomes more and more important.This paper presents a method for continuous noninvasive measurement of blood pressure based on long-term recursive convolution network.Firstly,the pulse wave signal collected by optical capacitance product method is normalized,threshold processing and feature extraction,and then the blood pressure is calculated from the pulse wave by long-term recursive convolution network.The experimental results show that when the pulse wave signal of optical capacitance product is directly input,the average absolute error and mean square error of the method are increased by 56.00%and 73.25%respectively.When the characteristic parameters are used as input,the average absolute error and mean square error of the experiment are increased by 59.55%and 87.41%compared with the direct input of optical capacitance product pulse wave signal.Compared with the direct input,the experimental effect of characteristic parameter input is better,and the accurate measurement of blood pressure is realized.

关 键 词：血压测量 脉搏波 长期递归卷积网络 卷积神经网络 长短期记忆网络 

分 类 号：TN911.7[电子电信—通信与信息系统]