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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…

人工智能 · 计算机科学 2026-05-06 Guangkun Nie , Jiabao Zhu , Gongzheng Tang , Deyun Zhang , Shijia Geng , Qinghao Zhao , Shenda Hong

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…

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…

机器学习 · 计算机科学 2025-11-10 Juntong Ni , Saurabh Kataria , Shengpu Tang , Carl Yang , Xiao Hu , Wei Jin

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…

计算机视觉与模式识别 · 计算机科学 2025-11-07 Arfina Rahman , Mahesh Banavar

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…

机器学习 · 计算机科学 2023-03-27 Yuntong Zhang , Jingye Xu , Mimi Xie , Wei Wang , Keying Ye , Jing Wang , Dakai Zhu

Heart rate (HR) estimation from photoplethysmography (PPG) signals is a key feature of modern wearable devices for health and wellness monitoring. While deep learning models show promise, their performance relies on the availability of…

Photoplethysmography (PPG) is the leading non-invasive technique for monitoring biosignals and cardiovascular health, with widespread adoption in both clinical settings and consumer wearable devices. While machine learning models trained on…

机器学习 · 计算机科学 2025-02-06 Arvind Pillai , Dimitris Spathis , Fahim Kawsar , Mohammad Malekzadeh

Photoplethysmography (PPG) refers to the measurement of variations in blood volume using light and is a feature of most wearable devices. The PPG signals provide insight into the body's circulatory system and can be employed to extract…

信号处理 · 电气工程与系统科学 2024-01-17 Yuyang Miao , Harry J. Davies , Danilo P. Mandic

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…

信号处理 · 电气工程与系统科学 2024-12-24 Manuel Meier , Christian Holz

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…

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…

信号处理 · 电气工程与系统科学 2025-08-15 Giulio Basso , Xi Long , Reinder Haakma , Rik Vullings

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…

信号处理 · 电气工程与系统科学 2025-03-19 Sara Maria Pagotto , Federico Tognoni , Matteo Rossi , Dario Bovio , Caterina Salito , Luca Mainardi , Pietro Cerveri

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…

信号处理 · 电气工程与系统科学 2025-09-26 Guangkun Nie , Qinghao Zhao , Gongzheng Tang , Yaxin Li , Shenda Hong

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…

机器学习 · 计算机科学 2025-12-10 Kanav Arora , Girish Narayanswamy , Shwetak Patel , Richard Li

Photoplethysmography (PPG) is a widely used non-invasive physiological sensing technique, suitable for various clinical applications. Such clinical applications are increasingly supported by machine learning methods, raising the question of…

Photoplethysmography (PPG) is one of the most widely captured biosignals for clinical prediction tasks, yet PPG-based algorithms are typically trained on small-scale datasets of uncertain quality, which hinders meaningful algorithm…

机器学习 · 计算机科学 2026-03-24 Mohammad Moulaeifard , Philip J. Aston , Peter H. Charlton , Nils Strodthoff

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…

Anemia is a prevalent hematological disorder that requires frequent hemoglobin monitoring for early diagnosis and effective management. Conventional hemoglobin assessment relies on invasive blood sampling, limiting its suitability for…

计算机与社会 · 计算机科学 2026-02-20 Garima Sahu , Poorva Verma , Nachiket Tapas

We develop an algorithm that accurately detects Atrial Fibrillation (AF) episodes from photoplethysmograms (PPG) recorded in ambulatory free-living conditions. We collect and annotate a dataset containing more than 4000 hours of PPG…

医学物理 · 物理学 2018-11-29 Maxime Voisin , Yichen Shen , Alireza Aliamiri , Anand Avati , Awni Hannun , Andrew Ng

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…

人机交互 · 计算机科学 2025-04-17 Manh Pham Hung , Matthew Yiwen Ho , Yiming Zhang , Dimitris Spathis , Aaqib Saeed , Dong Ma
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