photoplethysmogram
PulseAugur coverage of photoplethysmogram — every cluster mentioning photoplethysmogram across labs, papers, and developer communities, ranked by signal.
5 day(s) with sentiment data
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Huawei WATCH D3 launches with innovative 'lightly disturbing' blood pressure monitoring
Huawei has launched its new WATCH D3, a smartwatch designed for advanced health monitoring, particularly focusing on blood pressure management. The device features an innovative 'lightly disturbing dynamic blood pressur…
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New hybrid AI framework improves personalized blood pressure estimation
Researchers have developed a new hybrid framework for estimating blood pressure using photoplethysmography (PPG) signals. This approach combines a convolutional neural network (CNN) with a morphology-prior branch to cap…
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AI model predicts in-hospital stroke risk using PPG data
Researchers have developed a method to classify in-hospital stroke risk states using photoplethysmography (PPG) derived hemodynamic features. By analyzing continuous monitoring data from patients who experienced stroke …
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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…
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SKG Health partners with Peking Union Medical College for sleep apnea detection research
SKG Health and Peking Union Medical College have signed a collaboration agreement to research and develop algorithms for detecting sleep apnea. This research will involve multi-center clinical validation across three to…
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New framework enhances cardiovascular sensing with adaptive resource allocation
Researchers have developed a new framework called Physiological Information Reliability (PIR) to improve the accuracy and efficiency of cardiovascular sensing systems. PIR uses a contextual bandit approach to adapt sens…
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Camera rPPG accuracy varies by physiological property and observation conditions
A new research paper explores the recoverability of physiological properties from camera-derived remote photoplethysmography (rPPG) compared to contact photoplethysmography (PPG). The study, using the Multi-Domain Mobil…
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CardioFusion-AI framework enhances ECG-PPG fusion for robust physiological monitoring
Researchers have developed CardioFusion-AI, a novel framework for fusing electrocardiogram (ECG) and photoplethysmogram (PPG) signals for more robust physiological monitoring. This system is designed to overcome the ind…
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New P2E-VQ framework augments PPG data with ECG-linked representations
Researchers have developed P2E-VQ, a novel framework that enhances photoplethysmogram (PPG) data by linking it with electrocardiography (ECG) information. Instead of attempting to reconstruct ECG signals from PPG, P2E-V…
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Samsung AI models enable real-time smartwatch cardiac diagnostics
Samsung Research America has introduced two new AI models, xMAE and HiMAE, designed for on-device interpretation of electrocardiogram (ECG) and photoplethysmogram (PPG) data. These models enable advanced cardiac diagnos…
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Samsung unveils AI models for wearable health data analysis
Samsung Research America has developed two AI foundation models, xMAE and HiMAE, designed to analyze biosignal data from wearable devices. These models utilize self-supervised learning to extract insights from unlabeled…
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CardioState-JEPA integrates ECG, PPG, and PCG for unified cardiac representation
Researchers have developed CardioState-JEPA, a novel foundation model designed to learn a unified cardiac representation by integrating data from electrocardiography (ECG), photoplethysmography (PPG), and phonocardiogra…
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New ProtoMM Framework Enhances Self-Supervised Multimodal Biosignal Learning
Researchers have introduced ProtoMM, a new self-supervised learning framework designed to improve the modeling of multimodal time-series data, particularly in biosignals. Unlike existing methods that can overfit to easi…
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New AI frameworks enhance sleep staging accuracy using detailed signal analysis · 2 sources tracked
Researchers are developing advanced methods for automated sleep staging, moving beyond traditional 30-second epoch analysis. One approach utilizes Hidden Semi-Markov Models to convert coarse epoch labels into second-lev…
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PPG blood glucose models fail real-world tests, study finds
A new evaluation pipeline for non-invasive blood glucose level estimation using photoplethysmography (PPG) has revealed significant overestimation of model performance. When tested with stricter, participant-aware proto…
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Cardiologent: Multi-agent AI system aids arrhythmia assessment and management
Researchers have developed Cardiologent, a multi-agent clinical decision support system designed to assess patient-level arrhythmia, urgency, and management. Unlike previous systems that focus on single ECG readings or …
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New AI model screens aortic valve disease using PPG signals
Researchers have developed a novel Physiology-Guided Self-Supervised Learning (PG-SSL) method to screen for aortic valve disease (AVD) using photoplethysmography (PPG) signals. This approach leverages approximately 170,…
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New research suggests direct PPG signals are superior for wearable blood pressure monitoring
Two new research papers explore methods for estimating blood pressure using wearable sensors, focusing on photoplethysmography (PPG) and electrocardiography (ECG) signals. The first paper proposes a lightweight hybrid l…
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Bio-Tuning Glasses: Invisible Biofeedback Interface Adapts Environment Using Edge AI
Researchers are developing Bio-Tuning Glasses, an experimental concept for an invisible biofeedback interface that adapts the user's environment based on their physiological state. Unlike typical wearables that notify u…
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Google Research unveils SensorFM, a foundation model for wearable health data · 4 sources tracked
Google Research has introduced SensorFM, a large foundation model for wearable health data. Pre-trained on over a trillion minutes of sensor data from five million individuals, SensorFM learns a general representation o…