Advances in Cuffless Continuous Blood Pressure Monitoring Technology Based on PPG Signals

doi:10.1155/2022/8094351

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 生物识别与安全技术

	Advances in Cuffless Continuous Blood Pressure Monitoring Technology Based on PPG Signals
	Qin, Caijie 1,2,3; Wang, Xiaohua 4; Xu, Guangjun 5; Ma, Xibo2,3,6
发表期刊	BIOMED RESEARCH INTERNATIONAL
ISSN	2314-6133
	2022-10-01
卷号	2022 页码:16
通讯作者	Ma, Xibo(xibo.ma@ia.ac.cn)
摘要	Objective. To review the progress of research on photoplethysmography- (PPG-) based cuffless continuous blood pressure monitoring technologies and prospect the challenges that need to be addressed in the future. Methods. Using Web of Science and PubMed as search engines, the literature on cuffless continuous blood pressure studies using PPG signals in the recent five years were searched. Results. Based on the retrieved literature, this paper describes the available open datasets, commonly used signal preprocessing methods, and model evaluation criteria. Early researches employed multisite PPG signals to calculate pulse wave velocity or time and predicted blood pressure by a simple linear equation. Later, extensive researches were dedicated to mine the features of PPG signals related to blood pressure and regressed blood pressure by machine learning models. Most recently, many researches have emerged to experiment with complex deep learning models for blood pressure prediction with the raw PPG signal as input. Conclusion. This paper summarized the methods in the retrieved literature, provided insight into the artificial intelligence algorithms employed in the literature, and concluded with a discussion of the challenges and opportunities for the development of cuffless continuous blood pressure monitoring technologies.
DOI	10.1155/2022/8094351
关键词[WOS]	PHOTOPLETHYSMOGRAPHY ; WAVE ; PREDICTION ; ACCURACY
收录类别	SCI
语种	英语
资助项目	National Key Research Programs of China[2016YFA0100900] ; National Key Research Programs of China[2016YFA0100902] ; Chinese National Natural Science Foundation[82090051] ; Chinese National Natural Science Foundation[81871442] ; Youth Innovation Promotion Association CAS[Y201930] ; Educational Research Project for Young and Middle-aged Teachers in Fujian Province[JT180513] ; Scientific Research and Development Fund project of Sanming University[B201824] ; Fujian Key Lab of Agriculture IOT Application ; IOT Application Engineering Research Center of Fujian Province Colleges and Universities ; Digital Fujian Research Institute for Industrial Energy Big Data ; Laboratory for the Analysis and Application of Industry Big Data
项目资助者	National Key Research Programs of China ; Chinese National Natural Science Foundation ; Youth Innovation Promotion Association CAS ; Educational Research Project for Young and Middle-aged Teachers in Fujian Province ; Scientific Research and Development Fund project of Sanming University ; Fujian Key Lab of Agriculture IOT Application ; IOT Application Engineering Research Center of Fujian Province Colleges and Universities ; Digital Fujian Research Institute for Industrial Energy Big Data ; Laboratory for the Analysis and Application of Industry Big Data
WOS研究方向	Biotechnology & Applied Microbiology ; Research & Experimental Medicine
WOS类目	Biotechnology & Applied Microbiology ; Medicine, Research & Experimental
WOS记录号	WOS:000868606200002
出版者	HINDAWI LTD
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/50303
专题	多模态人工智能系统全国重点实验室_生物识别与安全技术
通讯作者	Ma, Xibo
作者单位	1.Sanming Univ, Inst Informat Engn, Sanming, Peoples R China 2.Chinese Acad Sci, Inst Automation, CBSR, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Automation, NLPR, Beijing, Peoples R China 4.Chinese Peoples Liberat Army Gen Hosp, Med Ctr 2, Dept Nephrol, Beijing, Peoples R China 5.Agr Bank China, Data Ctr, Beijing 100049, Peoples R China 6.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
第一作者单位	中国科学院自动化研究所; 模式识别国家重点实验室
通讯作者单位	中国科学院自动化研究所; 模式识别国家重点实验室
推荐引用方式 GB/T 7714	Qin, Caijie,Wang, Xiaohua,Xu, Guangjun,et al. Advances in Cuffless Continuous Blood Pressure Monitoring Technology Based on PPG Signals[J]. BIOMED RESEARCH INTERNATIONAL,2022,2022:16.
APA	Qin, Caijie,Wang, Xiaohua,Xu, Guangjun,&Ma, Xibo.(2022).Advances in Cuffless Continuous Blood Pressure Monitoring Technology Based on PPG Signals.BIOMED RESEARCH INTERNATIONAL,2022,16.
MLA	Qin, Caijie,et al."Advances in Cuffless Continuous Blood Pressure Monitoring Technology Based on PPG Signals".BIOMED RESEARCH INTERNATIONAL 2022(2022):16.