10 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…
MSPM: A Multi-Site Physiological Monitoring Dataset for Remote Pulse, Respiration, and Blood Pressure Estimation
Jeremy Speth, Nathan Vance, Benjamin Sporrer +3
Visible-light cameras can capture subtle physiological biomarkers without physical contact with the subject. We present the Multi-Site Physiological Monitoring (MSPM) dataset, whic…
Refining Remote Photoplethysmography Architectures using CKA and Empirical Methods
Nathan Vance, Patrick Flynn
Model architecture refinement is a challenging task in deep learning research fields such as remote photoplethysmography (rPPG). One architectural consideration, the depth of the m…
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…