Photoplethysmography
PulseAugur coverage of Photoplethysmography — every cluster mentioning Photoplethysmography across labs, papers, and developer communities, ranked by signal.
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New CAP method enhances PPG representation learning with clinical data
Researchers have developed a new method called Clinical Anchored Pretraining for PPG (CAP) to improve the learning of universal representations for photoplethysmography (PPG) signals. Existing methods often overlook pat…
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New PPG foundation model uses multimodal signals for improved robustness
Researchers have developed a new foundation model for photoplethysmography (PPG) data that enhances robustness by utilizing multimodal physiological signals like electrocardiograms and respiratory data during pretrainin…
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New dataset captures physiological responses to ASMR and nature videos
Researchers have introduced REST-ASMR, a new multimodal dataset designed to capture physiological and behavioral responses to ASMR and nature videos. The dataset includes photoplethysmography (PPG) data, synchronized au…
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VAMP-Diff model enhances realism in physiological signal generation
Researchers have developed VAMP-Diff, a novel variational diffusion model designed to generate more realistic photoplethysmography (PPG) signals. This model integrates a temporal PPG encoder with a conditional diffusion…
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New deep learning model estimates cardiac output from PPG signals
Researchers have developed a novel deep learning model called CVAF-Net for estimating cardiac output from short photoplethysmography (PPG) signals. This model processes both raw PPG data and a feature sequence map, fusi…
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New theory grounds cardiac health monitoring in smartphone photoplethysmography
Researchers have developed Cardiac Stability Theory (CST), a new framework that defines cardiovascular health based on stability margins around a cardiac dynamical attractor. This theory leads to the Cardiac Stability I…