Related papers: A Reproducible Study on Remote Heart Rate Measurem…
Hypertension is a leading cause of morbidity and mortality worldwide. The ability to diagnose and treat hypertension in the ambulatory population is hindered by limited access and poor adherence to current methods of monitoring blood…
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…
As reinforcement learning (RL) achieves more success in solving complex tasks, more care is needed to ensure that RL research is reproducible and that algorithms herein can be compared easily and fairly with minimal bias. RL results are,…
Remote Photoplethysmography (rPPG) is a non-contact method that uses facial video to predict changes in blood volume, enabling physiological metrics measurement. Traditional rPPG models often struggle with poor generalization capacity in…
Many remote photoplethysmography (rPPG) estimation models have achieved promising performance in the training domain but often fail to accurately estimate physiological signals or heart rates (HR) in the target domains. Domain…
Remote measurement of physiological signals from videos is an emerging topic. The topic draws great interests, but the lack of publicly available benchmark databases and a fair validation platform are hindering its further development. For…
Vital signs, such as heart rate (HR), heart rate variability (HRV), respiratory rate (RR), are important indicators for a person's health. Vital signs are traditionally measured with contact sensors, and may be inconvenient and cause…
Remote photoplethysmography (rPPG) holds great promise for continuous heart-rate monitoring of drivers in intelligent vehicles. However, its performance is severely degraded by the highly dynamic illumination changes. A critical yet…
This study evaluates remote Photopletismography (rPPG) algorithms, Spatial Subspace Rotation (2SR), Chrominance-based method (CHROM), Plane-Orthogonal-to-Skin (POS), and Principal Component Analysis (PCA), applied to selected…
Remote photoplethysmography (rPPG) enables non-contact heart rate measurement from facial videos, but its performance is significantly degraded by facial motions such as speaking and head shaking. To address this issue, we propose two…
Machine learning algorithms designed to characterize, monitor, and intervene on human health (ML4H) are expected to perform safely and reliably when operating at scale, potentially outside strict human supervision. This requirement warrants…
Scientific research frequently involves the use of computational tools and methods. Providing thorough documentation, open-source code, and data -- the creation of reproducible computational research -- helps others understand a…
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…
Remote photoplethysmography (rPPG) is an attractive camera-based health monitoring method that can measure the heart rhythm from facial videos. Many well-established deep-learning models have been reported to measure heart rate (HR) and…
Remote photoplethysmography (rPPG) has been widely applied to measure heart rate from face videos. To increase the generalizability of the algorithms, domain generalization (DG) attracted increasing attention in rPPG. However, when rPPG is…
Photoplethysmography is a prevalent, non-invasive heart monitoring method. In this paper an implementation of photoplethysmography on the Raspberry Pi is presented. Two modulation techniques are discussed, which make possible to measure…
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…
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…
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…
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…