基于光电容积脉搏波的心血管疾病相关体征参数提取算法

Parameter Extraction Algorithm of Cardiovascular Disease Related Physical Signs Based on Photoplethysmography

摘要: 光电容积脉搏波(Photoplethysmography, PPG)中蕴含着人体脉搏信息，将其提取出来是实现快速、高精度、低成本心血管健康监测的前提。PPG脉搏信号在时域中存在典型特征点，分析这些特征点可求出脉搏周期、极值、波形特征量等信号的基本特征值，再通过各种衍生公式获得心率(HR)、血压(BP)、心输出量(CO)等体征参数，这些体征参数与心血管疾病密切相关，并可直接反映患者的健康状况，是临床心血管疾病早期诊断的重要依据。本文采用MATLAB软件给出了从PPG脉搏波信号中识别典型特征点和计算体征参数(HR、BP、SV、CO、TPR、AC)的算法流程，并将这种基于PPG信号的心血管体征信息参数提取算法用于真实人体PPG信号分析，该研究有望对心血管疾病的预警提供一种方便快捷的监测技术。

Abstract: Photoplethysmography (PPG) signal implicates human pulse in-formation, and its extraction is the premise of cardiovascular health monitoring in a rapid, precise and low-cost manner. The PPG pulse signal shows typical feature points in the time domain, by ana-lyzing them pulse waves’ features such as pulse period, typical peaks’ height and waveform charac-teristic quantity can be acquired, and the physical signs parameters can be obtained through re-lated derivative formulas, like heart rate (HR), blood pressure (BP) and cardiac output (CO), which have a close relationship with cardiovascular diseases (CVD) and can directly reflect the health sta-tus of patients, these physical signs parameters play an important role in the CVD’s early diagnosis. This paper uses MATLAB software to give the algorithm flow of identifying typical feature points and calculating physical signs parameters (HR, BP, SV, CO, TPR, AC) from PPG signal, and applies this cardiovascular sign information parameter extraction algorithm based on PPG signal to the analysis of real human PPG signal. This research is expected to provide a convenient and fast monitoring technology for the early warning of CVD.