Heart Rate Variability
18 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
SCAMPS: Synthetics for Camera Measurement of Physiological Signals
The use of cameras and computational algorithms for noninvasive, low-cost and scalable measurement of physiological (e. g., cardiac and pulmonary) vital signs is very attractive.
Remote Photoplethysmograph Signal Measurement from Facial Videos Using Spatio-Temporal Networks
Recent studies demonstrated that the average heart rate (HR) can be measured from facial videos based on non-contact remote photoplethysmography (rPPG).
Specific Differential Entropy Rate Estimation for Continuous-Valued Time Series
We introduce a method for quantifying the inherent unpredictability of a continuous-valued time series via an extension of the differential Shannon entropy rate.
Sleep quality prediction in caregivers using physiological signals
To address these issues, we propose a clinical decision support system to predict sleep quality based on trends of physiological signals in the deep sleep stage.
A persistent homology approach to heart rate variability analysis with an application to sleep-wake classification
The first step is capturing the shapes of time series from two different aspects -- {the PH's and hence persistence diagrams of its} sub-level set and Taken's lag map.
RPnet: A Deep Learning approach for robust R Peak detection in noisy ECG
Furthermore, the model was also evaluated on three other databases.
Video-based Remote Physiological Measurement via Cross-verified Feature Disentangling
Remote physiological measurements, e. g., remote photoplethysmography (rPPG) based heart rate (HR), heart rate variability (HRV) and respiration frequency (RF) measuring, are playing more and more important roles under the application scenarios where contact measurement is inconvenient or impossible.
Inter-Beat Interval Estimation with Tiramisu Model: A Novel Approach with Reduced Error
However, extracting IBIs from noisy signals is challenging since the morphology of the signal is distorted in the presence of the noise.
PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression
The proposed method learns an individual-specific predictive model from heterogeneous observations, and enables estimation of an optimal transport map that yields a push forward operation onto the demographic features for each task.
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.