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Photoplethysmography (PPG)

Photoplethysmography (PPG) is a non-invasive light-based method that has been used since the 1930s for monitoring cardiovascular activity.

Source: Non-contact transmittance photoplethysmographic imaging (PPGI) for long-distance cardiovascular monitoring

Papers

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Showing 76–100 of 148 papers

TitleStatusHype
Bootstrapping Vision-language Models for Self-supervised Remote Physiological Measurement—0
Camera PPG waveforms at the forehead—0
Can gamification reduce the burden of self-reporting in mHealth applications? A feasibility study using machine learning from smartwatch data to estimate cognitive load—0
Car-Driver Drowsiness Assessment through 1D Temporal Convolutional Networks—0
Remote Heart Rate Monitoring in Smart Environments from Videos with Self-supervised Pre-training—0
RRWaveNet: A Compact End-to-End Multi-Scale Residual CNN for Robust PPG Respiratory Rate Estimation—0
Signal Quality Assessment of Photoplethysmogram Signals using Quantum Pattern Recognition and lightweight CNN Architecture—0
SleepPPG-Net: a deep learning algorithm for robust sleep staging from continuous photoplethysmography—0
Stress Assessment with Convolutional Neural Network Using PPG Signals—0
SympCam: Remote Optical Measurement of Sympathetic Arousal—0
TAU: Modeling Temporal Consistency Through Temporal Attentive U-Net for PPG Peak Detection—0
TNANet: A Temporal-Noise-Aware Neural Network for Suicidal Ideation Prediction with Noisy Physiological Data—0
TransfoRhythm: A Transformer Architecture Conductive to Blood Pressure Estimation via Solo PPG Signal Capturing—0
Tri-Spectral PPG: Robust Reflective Photoplethysmography by Fusing Multiple Wavelengths for Cardiac Monitoring—0
Uncertainty-Aware PPG-2-ECG for Enhanced Cardiovascular Diagnosis using Diffusion Models—0
Unexpected sawtooth artifact in beat-to-beat pulse transit time measured from patient monitor data—0
User Authentication and Vital Signs Extraction from Low-Frame-Rate and Monochrome No-contact Fingerprint Captures—0
Using Photoplethysmography to Detect Real-time Blood Pressure Changes with a Calibration-free Deep Learning Model—0
Variability of morphology in beat-to-beat photoplethysmographic waveform quantified with unsupervised wave-shape manifold learning for clinical assessment—0
Video-based sympathetic arousal assessment via peripheral blood flow estimation—0
Visual Saliency Detection in Advanced Driver Assistance Systems—0
Wearable Accelerometer Foundation Models for Health via Knowledge Distillation—0
Uncertainty quantification with approximate variational learning for wearable photoplethysmography prediction tasks—0
Machine learning for triage of strokes with large vessel occlusion using photoplethysmography biomarkers—0
Mamba-based Deep Learning Approaches for Sleep Staging on a Wireless Multimodal Wearable System without Electroencephalography—0
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