计算机技术与发展2023，Vol.33Issue(12)：23-31,9.DOI:10.3969/j.issn.1673-629X.2023.12.004
基于光电信号生理参数预测研究综述
A Review of Prediction of Physiological Parameters Based on Photoplethysmography
摘要
Abstract
The research based on photoplethysmography(PPG)sensors is particularly well-liked due to its properties,such as small size and ease of wear.We seek to demonstrate the usefulness of PPG signal in the prediction of physiological parameters and introduce the re-search progress of traditional machine learning algorithms and deep learning algorithms on various physiological parameters.The use of multi-site disease prevention and health monitoring will be made easier thanks to the convenience of PPG collecting.We provide several physiological parameter estimation algorithms by summarizing the research findings of PPG in recent years,which support the advancement of diagnostic techniques.This paper is mainly carried out from three aspects.Firstly,the existing datasets containing PPG are sorted out to show the number of signals in different datasets and other types of signals included,to help researchers find and use datasets.Secondly,the data preprocessing methods are summarized,the advantages and disadvantages of different preprocessing methods are analyzed,and an improved method is proposed to reduce the external interference received by the PPG signal during the acquisition process.Finally,the prediction algorithms of different physiological parameters are compared,analyzed and summarized by sub-mod-ules.关键词
PPG/机器学习/生理参数/健康监测/预测Key words
photoplethysmography/machine learning/physiological parameter/health monitoring/prediction分类
信息技术与安全科学引用本文复制引用
陈宇斌,崔玉红,梁启军,邓皓明..基于光电信号生理参数预测研究综述[J].计算机技术与发展,2023,33(12):23-31,9.基金项目
国家自然科学基金地区项目(62062050) （62062050）
