Heart rate estimation
23 papers with code • 5 benchmarks • 7 datasets
RR interval detection and R peak detection from QRS complex
Benchmarks
These leaderboards are used to track progress in Heart rate estimation
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Libraries
Use these libraries to find Heart rate estimation models and implementations
UBFC-rPPG
MMSE-HR
VIPL-HR
V4V
MMPD
BUAA-MIHR dataset
Most implemented papers
DeepFakesON-Phys: DeepFakes Detection based on Heart Rate Estimation
This work introduces a novel DeepFake detection framework based on physiological measurement.
An Open Framework for Remote-PPG Methods and their Assessment
phuselab/pyVHR
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This paper presents a comprehensive framework for studying methods of pulse rate estimation relying on remote photoplethysmography (rPPG).
Self-supervised Representation Learning Framework for Remote Physiological Measurement Using Spatiotemporal Augmentation Loss
To address these problems, we present a novel self-supervised spatiotemporal learning framework for remote physiological signal representation learning, where there is a lack of labelled training data.
Instantaneous Physiological Estimation using Video Transformers
revanurambareesh/instantaneous_transformer
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It outperformed both shallow and deep learning based methods for instantaneous respiration rate estimation.
pyVHR: a Python framework for remote photoplethysmography
phuselab/pyVHR
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PeerJ Computer Science 2022
A number of effective methods relying on data-driven, model-based and statistical approaches have emerged in the past two decades.
Heart rate estimation in intense exercise videos
Existing work can robustly measure heart rate under some degree of motion by face tracking.
Demo: RhythmEdge: Enabling Contactless Heart Rate Estimation on the Edge
mxahan/rPPG_edge_implementation
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In this demo paper, we design and prototype RhythmEdge, a low-cost, deep-learning-based contact-less system for regular HR monitoring applications.
Tiny-HR: Towards an interpretable machine learning pipeline for heart rate estimation on edge devices
Further, a hybrid pipeline consisting of the upsampler and classifier, followed by a peak detection algorithm was developed.
Liquid Structural State-Space Models
A proper parametrization of state transition matrices of linear state-space models (SSMs) followed by standard nonlinearities enables them to efficiently learn representations from sequential data, establishing the state-of-the-art on a large series of long-range sequence modeling benchmarks.
Image Enhancement for Remote Photoplethysmography in a Low-Light Environment
Using collected dataset, we found 1) face detection algorithm cannot detect faces in video captured in low light conditions; 2) A decrease in the amplitude of the pulsatile signal will lead to the noise signal to be in the dominant position; and 3) the chrominance-based method suffers from the limitation in the assumption about skin-tone will not hold, and Green and ICA method receive less influence than POS in dark illuminance environment.
