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Deep learning and remote photoplethysmography powered advancements in contactless physiological measurement

文献类型：期刊论文

作者Chen, Wei1; Yi, Zhe1; Lim, Lincoln Jian Rong2,3; Lim, Rebecca Qian Ru4; Zhang, Aijie1; Qian, Zhen5; Huang, Jiaxing6,7; He, Jia6,7; Liu, Bo1,8
刊名FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
出版日期2024-07-17
卷号12页码:29
关键词artificial intelligence computer vision rPPG deep learning physiological measurement
ISSN号2296-4185
DOI10.3389/fbioe.2024.1420100
通讯作者Liu, Bo(drbobo7@sina.com)
英文摘要In recent decades, there has been ongoing development in the application of computer vision (CV) in the medical field. As conventional contact-based physiological measurement techniques often restrict a patient's mobility in the clinical environment, the ability to achieve continuous, comfortable and convenient monitoring is thus a topic of interest to researchers. One type of CV application is remote imaging photoplethysmography (rPPG), which can predict vital signs using a video or image. While contactless physiological measurement techniques have an excellent application prospect, the lack of uniformity or standardization of contactless vital monitoring methods limits their application in remote healthcare/telehealth settings. Several methods have been developed to improve this limitation and solve the heterogeneity of video signals caused by movement, lighting, and equipment. The fundamental algorithms include traditional algorithms with optimization and developing deep learning (DL) algorithms. This article aims to provide an in-depth review of current Artificial Intelligence (AI) methods using CV and DL in contactless physiological measurement and a comprehensive summary of the latest development of contactless measurement techniques for skin perfusion, respiratory rate, blood oxygen saturation, heart rate, heart rate variability, and blood pressure.
WOS关键词HEART-RATE ESTIMATION ; PULSE TRANSIT-TIME ; BLOOD-PRESSURE ESTIMATION ; RESPIRATORY RATE ; OXYGEN-SATURATION ; RATE-VARIABILITY ; ROBUST ; NONCONTACT ; SMARTPHONES ; NETWORK
资助项目Beijing Hospitals Authority Clinical medicine Development of special funding support[YGLX202314] ; National Natural Science Foundation of China[82272581] ; Yunnan Provincial Science and Technology Talents and Platform Project[202105AF150050] ; Beijing Hospitals Authority's Ascent Plan[DFL20240402] ; Beijing Municipal Health Commission[BJRITO-RDP-2024]
WOS研究方向Biotechnology & Applied Microbiology ; Engineering
语种英语
WOS记录号WOS:001283557200001
出版者FRONTIERS MEDIA SA
资助机构Beijing Hospitals Authority Clinical medicine Development of special funding support ; National Natural Science Foundation of China ; Yunnan Provincial Science and Technology Talents and Platform Project ; Beijing Hospitals Authority's Ascent Plan ; Beijing Municipal Health Commission
源URL[http://ir.ia.ac.cn/handle/173211/59406]  
专题模式识别国家重点实验室_计算生物学与机器智能
通讯作者Liu, Bo
作者单位1.Capital Med Univ, Beijing Jishuitan Hosp, Dept Hand Surg, Beijing, Peoples R China
2.Footscray Hosp, Dept Med Imaging, Western Hlth, Footscray, Vic, Australia
3.Univ Melbourne, Dept Surg, Melbourne, Vic, Australia
4.Singapore Gen Hosp, Dept Hand & Reconstruct Microsurg, Singapore City, Singapore
5.Beijing United Imaging Res Inst Intelligent Imagin, Inst Intelligent Diagnost, Beijing, Peoples R China
6.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
7.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
8.Beijing Res Inst Traumatol & Orthopaed, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Chen, Wei,Yi, Zhe,Lim, Lincoln Jian Rong,et al. Deep learning and remote photoplethysmography powered advancements in contactless physiological measurement[J]. FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY,2024,12:29.
APA Chen, Wei.,Yi, Zhe.,Lim, Lincoln Jian Rong.,Lim, Rebecca Qian Ru.,Zhang, Aijie.,...&Liu, Bo.(2024).Deep learning and remote photoplethysmography powered advancements in contactless physiological measurement.FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY,12,29.
MLA Chen, Wei,et al."Deep learning and remote photoplethysmography powered advancements in contactless physiological measurement".FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY 12(2024):29.

入库方式： OAI收割

来源：自动化研究所

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