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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…

Remote photoplethysmography (rPPG) captures cardiac signals from facial videos and is gaining attention for its diverse applications. While deep learning has advanced rPPG estimation, it relies on large, diverse datasets for effective…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Joaquim Comas , Federico Sukno

Smartwatches or fitness trackers have garnered a lot of popularity as potential health tracking devices due to their affordable and longitudinal monitoring capabilities. To further widen their health tracking capabilities, in recent years…

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,…

Wrist-worn smart devices are providing increased insights into human health, behaviour and performance through sophisticated analytics. However, battery life, device cost and sensor performance in the face of movement-related artefact…

Signal Processing · Electrical Eng. & Systems 2020-04-02 Eoin Brophy , Willie Muehlhausen , Alan F. Smeaton , Tomas E. Ward

Remote photoplethysmography (rPPG) is a non-contact technique for measuring cardiac signals from facial videos. High-quality rPPG pulse signals are urgently demanded in many fields, such as health monitoring and emotion recognition.…

Image and Video Processing · Electrical Eng. & Systems 2020-06-05 Rencheng Song , Huan Chen , Juan Cheng , Chang Li , Yu Liu , Xun Chen

Remote photoplethysmography (rPPG) is an emerging contactless physiological sensing technique that leverages subtle color variations in facial videos to estimate vital signs such as heart rate and respiratory rate. This non-invasive method…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Ba-Thinh Nguyen , Thach-Ha Ngoc Pham , Hoang-Long Duc Nguyen , Thi-Duyen Ngo , Thanh-Ha Le

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

Blood Pressure (BP) is one of the four primary vital signs indicating the status of the body's vital (life-sustaining) functions. BP is difficult to continuously monitor using a sphygmomanometer (i.e. a blood pressure cuff), especially in…

Machine Learning · Computer Science 2021-08-03 Ali Tazarv , Marco Levorato

The use of observed wearable sensor data (e.g., photoplethysmograms [PPG]) to infer health measures (e.g., glucose level or blood pressure) is a very active area of research. Such technology can have a significant impact on health…

Signal Processing · Electrical Eng. & Systems 2023-05-01 Suril Mehta , Nipun Kwatra , Mohit Jain , Daniel McDuff

Photoplethysmography (PPG) sensor in wearable and clinical devices provides valuable physiological insights in a non-invasive and real-time fashion. Specialized Foundation Models (FM) or repurposed time-series FMs are used to benchmark…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Saurabh Kataria , Ayca Ermis , Lovely Yeswanth Panchumarthi , Minxiao Wang , Xiao Hu

Smart wearables enable continuous tracking of established biomarkers such as heart rate, heart rate variability, and blood oxygen saturation via photoplethysmography (PPG). Beyond these metrics, PPG waveforms contain richer physiological…

Wearable measurements, such as those obtained by photoplethysmogram (PPG) sensors are highly susceptible to motion artifacts and noise, affecting cardiovascular measures. Chest-acquired PPG signals are especially vulnerable, with signal…

Signal Processing · Electrical Eng. & Systems 2025-03-19 Sara Maria Pagotto , Federico Tognoni , Matteo Rossi , Dario Bovio , Caterina Salito , Luca Mainardi , Pietro Cerveri

This paper addresses the increasingly prominent problem of anomaly detection in distributed systems. It proposes a detection method based on federated contrastive learning. The goal is to overcome the limitations of traditional centralized…

Machine Learning · Computer Science 2025-06-25 Renzi Meng , Heyi Wang , Yumeng Sun , Qiyuan Wu , Lian Lian , Renhan Zhang

Physiological responses are nowadays widely used to recognize the affective state of subjects in real-life scenarios. However, these data are intrinsically subject-dependent, making machine learning techniques for data classification not…

Signal Processing · Electrical Eng. & Systems 2022-02-24 Francesca Gasparini , Alessandra Grossi , Marta Giltri , Stefania Bandini

Remote photoplethysmography (rPPG) is a method for measuring a subjects heart rate remotely using a camera. Factors such as subject movement, ambient light level, makeup etc. complicate such measurements by distorting the observed pulse.…

Computer Vision and Pattern Recognition · Computer Science 2025-02-05 Alexey Protopopov

Continuous blood pressure (BP) estimation via photoplethysmography (PPG) remains a significant challenge, particularly in providing comprehensive cardiovascular insights for hypertensive complications. This study presents a novel…

Medical Physics · Physics 2025-04-24 Yaowen Zhang , Libera Fresiello , Peter H. Veltink , Dirk W. Donker , Ying Wang

Camera-based monitoring of vital signs, also known as imaging photoplethysmography (iPPG), has seen applications in driver-monitoring, perfusion assessment in surgical settings, affective computing, and more. iPPG involves sensing the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Vineet R Shenoy , Suhas Lohit , Hassan Mansour , Rama Chellappa , Tim K. Marks

Personalization aims to characterize individual preferences and is widely applied across many fields. However, conventional personalized methods operate in a centralized manner, potentially exposing raw data when pooling individual…

Machine Learning · Computer Science 2025-08-06 Hao Di , Yi Yang , Haishan Ye , Xiangyu Chang

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
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