Photoplethysmography (PPG) heart rate estimation
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Benchmarks
Most implemented
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement
Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement
Time series saliency maps: explaining models across multiple domains
KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch
Papers
Time series saliency maps: explaining models across multiple domains
Traditional saliency map methods, popularized in computer vision, highlight individual points (pixels) of the input that contribute the most to the model's output. However, in time-series they offer limited insights as s…
Explainable Artificial Intelligence (XAI)Interpretability Techniques for Deep LearningPhotoplethysmography (PPG) heart rate estimationSeizure Detection+2RF-BayesPhysNet: A Bayesian rPPG Uncertainty Estimation Method for Complex Scenarios
Remote photoplethysmography (rPPG) technology infers heart rate by capturing subtle color changes in facial skin using a camera, demonstrating great potential in non-contact heart rate measurement. However, measurement a…
Computational EfficiencyPhotoplethysmography (PPG) heart rate estimationVariational InferenceKID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch
Accurate extraction of heart rate from photoplethysmography (PPG) signals remains challenging due to motion artifacts and signal degradation. Although deep learning methods trained as a data-driven inference problem offe…
Data AugmentationDeep LearningHeart rate estimationPhotoplethysmography (PPG)+1BeliefPPG: Uncertainty-aware Heart Rate Estimation from PPG signals via Belief Propagation
We present a novel learning-based method that achieves state-of-the-art performance on several heart rate estimation benchmarks extracted from photoplethysmography signals (PPG). We consider the evolution of the heart ra…
Heart rate estimationPhotoplethysmography (PPG) heart rate estimationTime Series AnalysisTime Series Anomaly DetectionReal-Time Monitoring of User Stress, Heart Rate and Heart Rate Variability on Mobile Devices
Stress is considered to be the epidemic of the 21st-century. Yet, mobile apps cannot directly evaluate the impact of their content and services on user stress. We introduce the Beam AI SDK to address this issue. Using ou…
Heart rate estimationHeart Rate VariabilityMental Stress DetectionPhotoplethysmography (PPG)+2Detecting beats in the photoplethysmogram: benchmarking open-source algorithms
The photoplethysmogram (PPG) signal is widely used in pulse oximeters and smartwatches. A fundamental step in analysing the PPG is the detection of heartbeats. Several PPG beat detection algorithms have been proposed, al…
BenchmarkingPhotoplethysmography (PPG) beat detectionPhotoplethysmography (PPG) heart rate estimationRhythm