Annotation of ECG signals using deep learning, tensorflow’ Keras

Official and maintained implementation of the paper "Exploring Novel Algorithms for Atrial Fibrillation Detection by Driving Graduate Level Education in Medical Machine Learning" (ECG-DualNet) [Physiological Measurement 2022, EMBC 2023].

Machine Learning on ECG to predict heart-beat classification.

Measure an electrocardiogram (ECG) with an Arduino Uno and an Olimex-EKG-EMG-Shield and calculate the heart rate variability afterward.

Code to access the ECG data from Physionet using Python.

心电图的学习研究（业余）

Maps the STAFF III Database of ECG data annotations file from one line per patient to one line per file

심장질환 환자 ECG 데이터 분석을 위한 딥러닝 기법 설계 및 경량화 모델 구축

Simple tool to visualize heart rhythm as measured by apple watches.

This is a java swing GUI for collect ECG data on serial stream

This research addresses the critical domain of anomaly detection in real-time ECG signals, a pivotal aspect in healthcare monitoring. The study encompasses comprehensive data preprocessing, detailed analysis of ECG graphs, and the application of diverse machine learning models, including logistic regression, random forest, XGboost,LSTM.

This repository includes all the scripts developed during the Final Degree Project aiming to provide new insights in risk stratification of Brugada Sindrome through AI-based approaches.