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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
Visual Saliency Detection in Advanced Driver Assistance Systems—0
Contrastive Self-Supervised Learning Based Approach for Patient Similarity: A Case Study on Atrial Fibrillation Detection from PPG SignalCode0
Quality Assessment of Photoplethysmography Signals For Cardiovascular Biomarkers Monitoring Using Wearable Devices—0
An Embedded Auto-Calibrated Offset Current Compensation Technique for PPG/fNIRS System—0
Personalized Anomaly Detection in PPG Data using Representation Learning and Biometric Identification—0
A Self-Supervised Algorithm for Denoising Photoplethysmography Signals for Heart Rate Estimation from Wearables—0
Sparse learned kernels for interpretable and efficient medical time series processingCode1
ApSense: Data-driven Algorithm in PPG-based Sleep Apnea SensingCode0
Camera PPG waveforms at the forehead—0
Amplitude-Independent Machine Learning for PPG through Visibility Graphs and Transfer Learning—0
Predicting Cardiovascular Disease Risk using Photoplethysmography and Deep Learning—0
PPG Signals for Hypertension Diagnosis: A Novel Method using Deep Learning Models—0
Deep Learning Systems for Advanced Driving Assistance—0
Efficient and Direct Inference of Heart Rate Variability using Both Signal Processing and Machine Learning—0
PPG-based Heart Rate Estimation with Efficient Sensor Sampling and Learning Models—0
Motion Matters: Neural Motion Transfer for Better Camera Physiological MeasurementCode1
HDformer: A Higher Dimensional Transformer for Diabetes Detection Utilizing Long Range Vascular Signals—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
Greedy-optimized Approach for Interbeat Interval and Heart Rate Variability Daily Monitoring using Wearable PPG—0
Rapid Extraction of Respiratory Waveforms from Photoplethysmography: A Deep Encoder Approach—0
Learning From Alarms: A Robust Learning Approach for Accurate Photoplethysmography-Based Atrial Fibrillation Detection using Eight Million Samples Labeled with Imprecise Arrhythmia AlarmsCode1
Facial Video-based Remote Physiological Measurement via Self-supervised LearningCode1
Multi-Head Cross-Attentional PPG and Motion Signal Fusion for Heart Rate Estimation—0
Real-Time Monitoring of User Stress, Heart Rate and Heart Rate Variability on Mobile Devices—0
RRWaveNet: A Compact End-to-End Multi-Scale Residual CNN for Robust PPG Respiratory Rate Estimation—0
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