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Remote camera measurement of the blood volume pulse via photoplethysmography (rPPG) is a compelling technology for scalable, low-cost, and accessible assessment of cardiovascular information. Neural networks currently provide the…

Image and Video Processing · Electrical Eng. & Systems 2024-03-19 Björn Braun , Daniel McDuff , Christian Holz

A photoplethysmography (PPG) is an uncomplicated and inexpensive optical technique widely used in the healthcare domain to extract valuable health-related information, e.g., heart rate variability, blood pressure, and respiration rate. PPG…

Cardiovascular diseases are one of the most severe causes of mortality, taking a heavy toll of lives annually throughout the world. The continuous monitoring of blood pressure seems to be the most viable option, but this demands an invasive…

Signal Processing · Electrical Eng. & Systems 2022-09-27 Nabil Ibtehaz , Sakib Mahmud , Muhammad E. H. Chowdhury , Amith Khandakar , Mohamed Arselene Ayari , Anas Tahir , M. Sohel Rahman

Camera-based physiological monitoring, especially remote photoplethysmography (rPPG), is a promising tool for health diagnostics, and state-of-the-art pulse estimators have shown impressive performance on benchmark datasets. We argue that…

Computer Vision and Pattern Recognition · Computer Science 2023-03-14 Jeremy Speth , Nathan Vance , Benjamin Sporrer , Lu Niu , Patrick Flynn , Adam Czajka

Background: Photoplethysmography (PPG), increasingly available through wearable devices, provides a non-invasive means of monitoring human hemodynamics. In this study, we introduce artificial intelligence-derived photoplethysmography…

Signal Processing · Electrical Eng. & Systems 2025-09-26 Guangkun Nie , Qinghao Zhao , Gongzheng Tang , Yaxin Li , Shenda Hong

Remote photoplethysmography (rPPG) has gained significant attention in recent years for its ability to extract physiological signals from facial videos. While existing rPPG measurement methods have shown satisfactory performance in…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Qian Liang , Yan Chen , Yang Hu

Photoplethysmographic imaging is a camera-based solution for non-contact cardiovascular monitoring from a distance. This technology enables monitoring in situations where contact-based devices may be problematic or infeasible, such as…

Computer Vision and Pattern Recognition · Computer Science 2016-06-30 Robert Amelard , David A Clausi , Alexander Wong

This report is part of the Qumphy project (22HLT01 Qumphy) that is funded by the European Union and is dedicated to the development of measures to quantify the uncertainties associated with Machine Learning algorithms applied to medical…

Photoplethsmography (PPG)-based individual identification aiming at recognizing humans via intrinsic cardiovascular activities has raised extensive attention due to its high security and resistance to mimicry. However, this kind of…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Riling Wei , Hanjie Chen , Kelu Yao , Chuanguang Yang , Jun Wang , Chao Li

Smart watches and other wearable devices are equipped with photoplethysmography (PPG) sensors for monitoring heart rate and other aspects of cardiovascular health. However, PPG signals collected from such devices are susceptible to…

Signal Processing · Electrical Eng. & Systems 2023-07-12 Pranay Jain , Cheng Ding , Cynthia Rudin , Xiao Hu

Continuous cardiovascular monitoring can play a key role in precision health. However, some fundamental cardiac biomarkers of interest, including stroke volume and cardiac output, require invasive measurements, e.g., arterial pressure…

Photoplethysmography (PPG) is a non-invasive and economical technique to extract vital signs of the human body. Although it has been widely used in consumer and research grade wrist devices to track a user's physiology, the PPG signal is…

Signal Processing · Electrical Eng. & Systems 2021-09-08 Runyu Mao , Mackenzie Tweardy , Stephan W. Wegerich , Craig J. Goergen , George R. Wodicka , Fengqing Zhu

Blood pressure (BP) changes are linked to individual health status in both clinical and non-clinical settings. This study developed a deep learning model to classify systolic (SBP), diastolic (DBP), and mean (MBP) BP changes using…

Signal Processing · Electrical Eng. & Systems 2024-07-04 Jingyuan Hong , Manasi Nandi , Weiwei Jin , Jordi Alastruey

Analyzing the cardiovascular system condition via Electrocardiography (ECG) is a common and highly effective approach, and it has been practiced and perfected over many decades. ECG sensing is non-invasive and relatively easy to acquire,…

Smartwatches have become popular for monitoring physiological parameters outside clinical settings. Using reflective photoplethysmography (PPG) sensors, such watches can non-invasively estimate heart rate (HR) in everyday environments and…

Signal Processing · Electrical Eng. & Systems 2024-12-24 Manuel Meier , Christian Holz

Photoplethysmographic (PPG) signals offer diagnostic potential beyond heart rate analysis or blood oxygen level monitoring. In the recent past, research focused extensively on non-invasive PPG-based approaches to blood pressure (BP)…

Computer Vision and Pattern Recognition · Computer Science 2022-04-13 Fabian Schrumpf , Paul Rudi Serdack , Mirco Fuchs

Sleep monitoring through accessible wearable technology is crucial to improving well-being in ubiquitous computing. Although photoplethysmography(PPG) sensors are widely adopted in consumer devices, achieving consistently reliable sleep…

Signal Processing · Electrical Eng. & Systems 2025-08-06 Jiawei Wang , Yu Guan , Chen Chen , Ligang Zhou , Laurence T. Yang , Sai Gu

Photoplethysmography (PPG) is a simple and inexpensive technology used in many smart devices to monitor cardiovascular health. The PPG sensors use LED lights to penetrate into the bloodstream to detect the different blood volume changes in…

Medical Physics · Physics 2021-10-22 Irene Pi , Isleen Pi , Wei Wu

Remote photoplethysmography (rPPG) measurement enables non-contact physiological monitoring but suffers from accuracy degradation under head motion and illumination changes. Existing deep learning methods are mostly heuristic and lack…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Bo Zhao , Dan Guo , Junzhe Cao , Yong Xu , Bochao Zou , Tao Tan , Yue Sun , Zitong Yu

Remote photoplethysmography (rPPG) enables non-contact, continuous monitoring of physiological signals and offers a practical alternative to traditional health sensing methods. Although rPPG is promising for daily health monitoring, its…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Xulin Ma , Jiankai Tang , Zhang Jiang , Songqin Cheng , Yuanchun Shi , Dong LI , Xin Liu , Daniel McDuff , Xiaojing Liu , Yuntao Wang
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