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In recent years, deep learning methods have shown impressive results for camera-based remote physiological signal estimation, clearly surpassing traditional methods. However, the performance and generalization ability of Deep Neural…

Computer Vision and Pattern Recognition · Computer Science 2024-08-01 Joaquim Comas , Antonia Alomar , Adria Ruiz , Federico Sukno

Remote photoplethysmography (rPPG) offers a novel approach to noninvasive monitoring of vital signs, such as respiratory rate, utilizing a camera. Although several supervised and self-supervised methods have been proposed, they often fail…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Banafsheh Adami , Nima Karimian

Remote photoplethysmography (rPPG), which aims at measuring heart activities and physiological signals from facial video without any contact, has great potential in many applications (e.g., remote healthcare and affective computing). Recent…

Computer Vision and Pattern Recognition · Computer Science 2022-05-24 Zitong Yu , Yuming Shen , Jingang Shi , Hengshuang Zhao , Philip Torr , Guoying Zhao

The paper proposes accurate Blood Pressure Monitoring (BPM) based on a single-site Photoplethysmographic (PPG) sensor and provides an energy-efficient solution on edge cuffless wearable devices. Continuous PPG signal preprocessed and used…

Signal Processing · Electrical Eng. & Systems 2021-08-03 Wenrui Lin , Berken Utku Demirel , Mohammad Abdullah Al Faruque , G. P. Li

Hypertension is a potentially unsafe health ailment, which can be indicated directly from the Blood pressure (BP). Hypertension always leads to other health complications. Continuous monitoring of BP is very important; however, cuff-based…

Remote heart rate measurement is an increasingly concerned research field, usually using remote photoplethysmography (rPPG) to collect heart rate information through video data collection. However, in certain specific scenarios (such as low…

Image and Video Processing · Electrical Eng. & Systems 2024-06-06 Jianming Yu , Yuchen He , Bin Li , Hui Chen , Huaibin Zheng , Jianbin Liu , Zhuo Xu

Video-based remote photoplethysmography (rPPG) has emerged as a promising technology for non-contact vital sign monitoring, especially under controlled conditions. However, the accurate measurement of vital signs in real-world scenarios…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Nhi Nguyen , Le Nguyen , Honghan Li , Miguel Bordallo López , Constantino Álvarez Casado

In recent years, research about monitoring vital signs by smartphones grows significantly. There are some special sensors like Electrocardiogram (ECG) and Photoplethysmographic (PPG) to detect heart rate (HR) and respiration rate (RR).…

Image and Video Processing · Electrical Eng. & Systems 2021-06-08 Jafar Pourbemany , Almabrok Essa , Ye Zhu

Remote photoplethysmography (rPPG) enables non-contact physiological measurement from facial videos; however, its practical deployment is often hindered by substantial performance degradation under domain shift. While recent deep…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Ba-Thinh Nguyen , Thi-Duyen Ngo , Thanh-Trung Huynh , Thanh-Ha Le , Huy-Hieu Pham

Remote photoplethysmography (rPPG) is a non-contact technique that estimates physiological signals by analyzing subtle skin color changes in facial videos. Existing rPPG methods often encounter performance degradation under facial motion…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Zuxian He , Xu Cheng , Zhaodong Sun , Haoyu Chen , Jingang Shi , Xiaobai Li , Guoying Zhao

Remote estimation of vital signs enables health monitoring for situations in which contact-based devices are either not available, too intrusive, or too expensive. In this paper, we present a modular, interpretable pipeline for pulse signal…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Vineet R. Shenoy , Shaoju Wu , Armand Comas , Tim K. Marks , Suhas Lohit , Hassan Mansour

Remote Photoplethysmography (rPPG) enables convenient non-contact physiological measurement. Existing Self-Supervised Learning (SSL) methods commonly fall into a correlation trap: they tend to learn the most dominant periodic signals in the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Zhiyi Niu , Xiaoguang Tu , Bo Zhao , Junzhe Cao , Dan Guo , Zitong Yu

Vital signs such as pulse rate and breathing rate are currently measured using contact probes. But, non-contact methods for measuring vital signs are desirable both in hospital settings (e.g. in NICU) and for ubiquitous in-situ health…

Computer Vision and Pattern Recognition · Computer Science 2015-03-25 Mayank Kumar , Ashok Veeraraghavan , Ashutosh Sabharval

Objective: to establish an algorithmic framework and a benchmark dataset for comparing methods of pulse rate estimation using imaging photoplethysmography (iPPG). Approach: first we reveal essential steps of pulse rate estimation from…

Image and Video Processing · Electrical Eng. & Systems 2018-05-01 Anton M. Unakafov

Heart Rate Variability (HRV) measures the variation of the time between consecutive heartbeats and is a major indicator of physical and mental health. Recent research has demonstrated that photoplethysmography (PPG) sensors can be used to…

Machine Learning · Computer Science 2023-03-27 Yuntong Zhang , Jingye Xu , Mimi Xie , Dakai Zhu , Houbing Song , Wei Wang

Remote photoplethysmography (rPPG) based on traditional frame-based cameras often struggles with motion artifacts and limited temporal resolution. To address these limitations, we introduce EMPD (Event-based Multimodal Physiological…

Signal Processing · Electrical Eng. & Systems 2026-03-31 Qian Feng , Pengfei Li , Rongshan Gao , Jiale Xu , Rui Gong , Yidi Li

Hypertension is a medical condition characterized by high blood pressure, and classifying it into its various stages is crucial to managing the disease. In this project, a novel method is proposed for classifying stages of hypertension…

Machine Learning · Computer Science 2023-04-17 Graham Frederick , Yaswant T , Brintha Therese A

Heart rate estimation from photoplethysmography (PPG) signals generated by wearable devices such as smartwatches and fitness trackers has significant implications for the health and well-being of individuals. Although prior work has…

Machine Learning · Computer Science 2025-12-10 Kanav Arora , Girish Narayanswamy , Shwetak Patel , Richard Li

Objective: Evaluate a method for the estimation of the nocturnal systolic blood pressure (SBP) dip from 24-hour blood pressure trends using a wrist-worn photoplethysmography (PPG) sensor and a deep neural network in free-living individuals,…

Wearable devices with photoplethysmography (PPG) sensors are widely used to monitor heart rate (HR), yet often suffer from accuracy issues. However, users typically do not receive an indication of potential measurement errors. We present a…