photoplethysmogram
PulseAugur coverage of photoplethysmogram — every cluster mentioning photoplethysmogram across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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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 model synthesizes physiological signals with parameter efficiency
Researchers have developed a new parameter-efficient foundation model called Compact Latent Manifold Translation (CLMT) for synthesizing physiological signals. This model addresses challenges like modality and frequency…
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New AI model xMAE learns biosignal timing for better health predictions
Researchers have developed a new pretraining framework called xMAE designed to learn meaningful representations from biosignals. This method specifically addresses the temporal dynamics between different biosignals, suc…
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Deep learning models show promise in pavement, aero-engine, and affect recognition tasks
Researchers are exploring deep learning models for predictive maintenance and performance analysis across various domains. One study utilizes CNN and LSTM networks with extensive pavement condition data from Texas to mo…
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New generative self-supervised learning framework improves physiological estimation from PPG data
Researchers have developed a new generative self-supervised learning framework called TS2TC to improve the estimation of physiological parameters from photoplethysmography (PPG) data. This framework addresses the challe…
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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…