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Objective. Wearable devices with embedded photoplethysmography (PPG) enable continuous non-invasive monitoring of cardiac activity, offering a promising strategy to reduce the global burden of cardiovascular diseases. However, monitoring…

Signal Processing · Electrical Eng. & Systems 2025-08-15 Giulio Basso , Xi Long , Reinder Haakma , Rik Vullings

Accurate extraction of heart rate from photoplethysmography (PPG) signals remains challenging due to motion artifacts and signal degradation. Although deep learning methods trained as a data-driven inference problem offer promising…

Signal Processing · Electrical Eng. & Systems 2024-10-21 Christodoulos Kechris , Jonathan Dan , Jose Miranda , David Atienza

Hearth Rate (HR) monitoring is increasingly performed in wrist-worn devices using low-cost photoplethysmography (PPG) sensors. However, Motion Artifacts (MAs) caused by movements of the subject's arm affect the performance of PPG-based HR…

Signal Processing · Electrical Eng. & Systems 2022-03-29 Alessio Burrello , Daniele Jahier Pagliari , Matteo Risso , Simone Benatti , Enrico Macii , Luca Benini , Massimo Poncino

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

Photoplethysmography (PPG) sensors allow for non-invasive and comfortable heart-rate (HR) monitoring, suitable for compact wrist-worn devices. Unfortunately, Motion Artifacts (MAs) severely impact the monitoring accuracy, causing high…

Recent studies showed that Photoplethysmography (PPG) sensors embedded in wearable devices can estimate heart rate (HR) with high accuracy. However, despite of prior research efforts, applying PPG sensor based HR estimation to embedded…

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

Photoplethysmogram (PPG) is increasingly used to provide monitoring of the cardiovascular system under ambulatory conditions. Wearable devices like smartwatches use PPG to allow long term unobtrusive monitoring of heart rate in free living…

Machine Learning · Computer Science 2019-03-22 Shyam A , Vignesh Ravichandran , Preejith S. P , Jayaraj Joseph , Mohanasankar Sivaprakasam

Photoplethysmography (PPG) is a non-invasive technology that measures changes in blood volume in the microvascular bed of tissue. It is commonly used in medical devices such as pulse oximeters and wrist worn heart rate monitors to monitor…

Photoplethysmography (PPG) signals, which measure changes in blood volume in the skin using light, have recently gained attention in biometric authentication because of their non-invasive acquisition, inherent liveness detection, and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Arfina Rahman , Mahesh Banavar

Photoplethysmography (PPG) is widely used in wearable health monitoring, yet large PPG foundation models remain difficult to deploy on resource-limited devices. We present PPG-Distill, a knowledge distillation framework that transfers both…

Machine Learning · Computer Science 2025-11-10 Juntong Ni , Saurabh Kataria , Shengpu Tang , Carl Yang , Xiao Hu , Wei Jin

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

Photoplethysmography (PPG) Sensors, widely deployed in smartwatches, offer a simple and non-invasive authentication approach for daily use. However, PPG authentication faces reliability issues due to motion artifacts from physical activity…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Jiankai Tang , Jiacheng Liu , Renling Tong , Kai Zhu , Zhe Li , Xin Yi , Junliang Xing , Yuanchun Shi , Yuntao Wang

Photoplethysmography (PPG) is a widely adopted, non-invasive technique for monitoring cardiovascular health and physiological parameters in both consumer and clinical settings. While motion artifacts in dynamic environments have been…

Human-Computer Interaction · Computer Science 2025-04-17 Manh Pham Hung , Matthew Yiwen Ho , Yiming Zhang , Dimitris Spathis , Aaqib Saeed , Dong Ma

Background: Photoplethysmography (PPG) is a non-invasive optical sensing technique widely used to capture hemodynamic information, with broad deployment in both clinical monitoring systems and wearable devices. In recent years, the…

Artificial Intelligence · Computer Science 2026-05-06 Guangkun Nie , Jiabao Zhu , Gongzheng Tang , Deyun Zhang , Shijia Geng , Qinghao Zhao , Shenda Hong

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

Cardiac abnormalities affecting heart rate and rhythm are commonly observed in both healthy and acutely unwell people. Although many of these are benign, they can sometimes indicate a serious health risk. ECG monitors are typically used to…

Signal Processing · Electrical Eng. & Systems 2018-07-12 Stewart Whiting , Samuel Moreland , Jason Costello , Glen Colopy , Christopher McCann

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

Digital twins for 1D bio-signals enable real-time monitoring of physiological processes of a person, which enables early disease diagnosis and personalized treatment. This work introduces a novel non-contact method for digital twin (DT)…

Objective- Heart rate monitoring using wrist type Photoplethysmographic (PPG) signals is getting popularity because of construction simplicity and low cost of wearable devices. The task becomes very difficult due to the presence of various…

In the context of epilepsy monitoring, EEG artifacts are often mistaken for seizures due to their morphological similarity in both amplitude and frequency, making seizure detection systems susceptible to higher false alarm rates. In this…

Signal Processing · Electrical Eng. & Systems 2022-04-21 Thorir Mar Ingolfsson , Andrea Cossettini , Simone Benatti , Luca Benini
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