文献类型：期刊文献

英文题名：Blood pressure prediction based on multi-sensor information fusion of electrocardiogram, photoplethysmography, and pressure pulse waveform

作者：Yan, Jianjun[1];Wang, Zeyu[1];Guo, Rui[2];Yan, Haixia[2];Wang, Yiqin[2];Qiu, Wenbo[1]

机构：[1]East China Univ Sci & Technol, Shanghai Key Lab Intelligent Sensing & Detect Tech, Shanghai 200237, Peoples R China;[2]Shanghai Univ Tradit Chinese Med, Sch Tradit Chinese Med, Shanghai Key Lab Hlth Identificat & Assessment, Shanghai 201203, Peoples R China

年份：2025

卷号：240

外文期刊名：MEASUREMENT

收录：;EI(收录号：20243516943353);WOS:【SCI-EXPANDED(收录号:WOS:001303344300001)】；

基金：This work was supported by the National Natural Science Foundation of China [grant number 82074332] and the Shanghai Science and Technology Committee funding [grant number 19441901100] .

语种：英文

外文关键词：Electrocardiogram; Photoplethysmography; Pressure pulse waveform; Blood pressure prediction; Information fusion; Multi-sensor

摘要：Cardiovascular diseases are now the leading cause of death that endangers people's health. Thus, a precise and reliable blood pressure (BP) prediction method is essential. This paper proposes a noninvasive BP prediction method with the multi-feature fusion of electrocardiogram (ECG), photoplethysmography (PPG), and pressure pulse waveform (PPW). A multi-sensor information acquisition platform was developed to collect cardiovascularrelated signals. Besides, the algorithms were designed to clean, preprocess, and extract features from sample data. Furthermore, the BP prediction model was constructed by using feature selection and feature fusion based on Random Forest Regression (RFR). Finally, the importance of features used for blood pressure prediction was analyzed, and the results of RFR-based blood pressure prediction were compared with those of other machine learning algorithms. The mean absolute errors of systolic and diastolic blood pressure prediction reached 0.90 mmHg and 2.47 mmHg, respectively. The results of the BP prediction model based on multi-sensor information fusion meet both the AAMI and BHS standards.