2 citations · 5 across the 6 of their papers we have counts for
6 papers
SiNC+: Adaptive Camera-Based Vitals with Unsupervised Learning of Periodic Signals
Jeremy Speth, Nathan Vance, Patrick Flynn +1
Subtle periodic signals, such as blood volume pulse and respiration, can be extracted from RGB video, enabling noncontact health monitoring at low cost. Advancements in remote puls…
Measuring Domain Shifts using Deep Learning Remote Photoplethysmography Model Similarity
Nathan Vance, Patrick Flynn
Domain shift differences between training data for deep learning models and the deployment context can result in severe performance issues for models which fail to generalize. We s…
Promoting Generalization in Cross-Dataset Remote Photoplethysmography
Nathan Vance, Jeremy Speth, Benjamin Sporrer +1
Remote Photoplethysmography (rPPG), or the remote monitoring of a subject's heart rate using a camera, has seen a shift from handcrafted techniques to deep learning models. While c…
Full-Body Cardiovascular Sensing with Remote Photoplethysmography
Lu Niu, Jeremy Speth, Nathan Vance +3
Remote photoplethysmography (rPPG) allows for noncontact monitoring of blood volume changes from a camera by detecting minor fluctuations in reflected light. Prior applications of…
Non-Contrastive Unsupervised Learning of Physiological Signals from Video
Jeremy Speth, Nathan Vance, Patrick Flynn +1
Subtle periodic signals such as blood volume pulse and respiration can be extracted from RGB video, enabling remote health monitoring at low cost. Advancements in remote pulse esti…
Hallucinated Heartbeats: Anomaly-Aware Remote Pulse Estimation
Jeremy Speth, Nathan Vance, Benjamin Sporrer +3
Camera-based physiological monitoring, especially remote photoplethysmography (rPPG), is a promising tool for health diagnostics, and state-of-the-art pulse estimators have shown i…