Using deep learning to detect Atrial fibrillation
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Updated
Mar 7, 2019 - Jupyter Notebook
Using deep learning to detect Atrial fibrillation
Some simple experiments code of Biomedical.
An iOS fall detection data collection system. It uses CoreMotion for retrieving accelerometer, magnetometer, and gyroscope sensors, and interfaces with a PolarH10 chest strap for ECG data using the Polar SDK.
Public repository associated with: Assessing The Effect of Various Sampling Frequency and Double Soft F1-loss in Multi-Label Classification of 12-Lead ECGs
A repository related to a master thesis in electronics, informatics and technology. Title: "Comparing Cardiological and Algorithm-Based ECG Interpretation in Athletes: Can Artificial Intelligence Improve the Algorithms?"
The repository contains the project https://github.com/mk590901/graph_widget: ported on Jetpack Compose the widget for visualization ECG.
This repository is about the source codes of an explainable algorithm for detecting drug-induced QT-prolongation at risk of torsades de pointes (TdP) regardless of heart rate and T-wave morphology, its comparison with a rule-based decision tree model and the data analysis underpinning the findings reported in the preprint paper submitted to the …
ECG Classification usign Neural Networks
Course project for EE338 - Digital Signal Processing
This repository is associated with Multi-Label ECG Classification Using Convolutional Neural Networks in a Classifier Chain
R function for the detection of qrs waves
Processing bioelectrical signals and medical images
ECG with ad8232 module.
This project involves creating a MATLAB script that features a graphical user interface (GUI) for processing ECG data. Users can select an ECG file, visualize the data through plotting, and calculate the heart rate based on the R-R interval formula. Additionally, the script includes functionality to detect signs of myocardial dysfunction.
SigXNet for Electrical Activity Signal Classification (ECG & EEG)
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