Detection of Cardiac Waveforms Using Remote Photoplethysmogram Technology
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Updated
Apr 22, 2024 - Python
Detection of Cardiac Waveforms Using Remote Photoplethysmogram Technology
Model development for understanding the relationship between photoplethysmography (PPG) waveforms and physiological parameters of Dengue patients.
This repository contains last developments on the detection of the heart rate (HR) by using a kinect.
Python app to take photoplethysmography to detect heartbeat based on webcam feed.
The dataset used for the "Non-Contact Blood Pressure Estimation using infrared motion magnified facial video" publication. The code developed is to fit the data to the reference Blood Pressure values.
ICIP 2019 - Determining Heart Rate from Facial Video - Robust to motion and illumination interferences!
The dataset used for the "A non-contact SpO2 estimation using video magnification and infrared data" publication
Estimate vital signs such as heart rate and respiratory rate from video.
Using self-supervised learning to extract features from PPG signals
Remote photoplethysmography (rPPG) is a contactless method to monitor human cardiac activities by detecting the pulse-induced subtle color variations on the human skin surface using a multi-wavelength RGB camera. By measuring the variance of red, green, and blue light reflection changes from the skin, as the contrast between specular reflection …
real-time application for video-based methods in the context of MRI
Systole: A python package for cardiac signal synchrony and analysis
A package for processing signals recorded using wearable sensors, such as Electrocardiogram (ECG), Photoplethysmogram (PPG), Electrodermal activity (EDA) and 3-axis acceleration (ACC).
MMPD: Multi-Domain Mobile Video Physiology Dataset(EMBC2023 Oral)
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