Heart Rate Variability
16 papers with code • 0 benchmarks • 3 datasets
Heart rate variability (HRV) is the physiological phenomenon of variation in the time interval between heartbeats. It is measured by the variation in the beat-to-beat interval.
Benchmarks
These leaderboards are used to track progress in Heart Rate Variability
Most implemented papers
pyVHR: a Python framework for remote photoplethysmography
A number of effective methods relying on data-driven, model-based and statistical approaches have emerged in the past two decades.
Facial Video-based Remote Physiological Measurement via Self-supervised Learning
Facial video-based remote physiological measurement aims to estimate remote photoplethysmography (rPPG) signals from human face videos and then measure multiple vital signs (e. g. heart rate, respiration frequency) from rPPG signals.
Pan-Tompkins++: A Robust Approach to Detect R-peaks in ECG Signals
However, the performance of the Pan-Tompkins algorithm in detecting the QRS complexes degrades in low-quality and noisy signals.
CardiacGen: A Hierarchical Deep Generative Model for Cardiac Signals
We present CardiacGen, a Deep Learning framework for generating synthetic but physiologically plausible cardiac signals like ECG.
Accelerated Sample-Accurate R-Peak Detectors Based on Visibility Graphs
Further acceleration is obtained by adopting the computationally efficient horizontal visibility graph, which has not yet been used for R-peak detection.
Conversational Health Agents: A Personalized LLM-Powered Agent Framework
openCHA includes an orchestrator to plan and execute actions for gathering information from external sources, essential for formulating responses to user inquiries.