Photoplethysmography
PulseAugur coverage of Photoplethysmography — every cluster mentioning Photoplethysmography across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
-
New simulation method improves cardiovascular biomarker estimation with BCG signals
Researchers have developed a simulation-based inference method to estimate cardiovascular biomarkers using non-invasive biosignals. By employing a whole-body cardiovascular circulation model, they generated synthetic ph…
-
New SIFPBPNet model improves cuffless blood pressure estimation
Researchers have developed a novel dual-path network called SIFPBPNet for estimating blood pressure using wearable photoplethysmography (PPG) signals. This network addresses population heterogeneity by separately proces…
-
Apple Watch updates Health Sensing System with new heart sensors
Apple has unveiled its new Health Sensing System for the Apple Watch, incorporating enhanced electrical and optical heart sensors. This system utilizes photoplethysmography (PPG) technology and advanced signal processin…
-
New framework improves blood pressure estimation during fluctuations
Researchers have developed a new framework for evaluating and re-calibrating blood pressure estimation models that use photoplethysmography (PPG). This approach focuses on identifying and analyzing performance during ab…
-
SSL representations insufficient for subjective emotion detection, study finds
A new research paper explores the limitations of general self-supervised learning (SSL) representations when applied to subjective tasks like emotion detection using photoplethysmography (PPG) signals. While these repre…
-
New model learns unified cardiac representation from multiple sensor types
Researchers have developed CardioState-JEPA, a novel foundation model designed to learn a unified representation of cardiac physiology from multiple sensor modalities. This model integrates data from electrocardiography…
-
Deep learning model classifies age using pulse wave images
Researchers have developed a novel deep learning approach using convolutional neural networks to classify arterial pulse waves into age groups. By transforming time-series pulse wave data into images via the Symmetric P…
-
New PECS framework improves concept drift detection for cardiovascular AI
Researchers have developed a new framework called PECS to detect concept drift in multimodal physiological signals for cardiovascular AI models. This framework compares changes within the model to measurable changes in …
-
PPG-based blood glucose estimation methods fail under rigorous evaluation
A new research paper published on arXiv evaluates the feasibility of estimating blood glucose levels using photoplethysmography (PPG) signals. The study developed a reproducible evaluation pipeline and found that existi…
-
Smartwatch detects silent heart attack, saving owner's life
A high-end Smart Health Watch with advanced ECG and Photoplethysmography (PPG) sensors alerted Elena Rostova to a silent heart attack. The watch detected a high heart rate and signs of acute cardiac distress, prompting …
-
New framework reconstructs low-quality PPG signals for accurate SpO2 estimation
Researchers have developed a novel framework for reconstructing low-quality dual-wavelength photoplethysmography (PPG) signals, crucial for continuous oxygen saturation (SpO2) estimation in wearable health monitoring. T…
-
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…
-
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…
-
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…
-
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…
-
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…
-
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…