A demo application using LightningChart JS to display ECG data.

Example showcasing Line Series feature for coloring line dynamically based on X coordinates

❤️ Predict heart disease risk with an advanced machine learning pipeline, featuring data preprocessing, model tuning, and an interactive web interface.

A Unified Framework for Benchmarking Generative Electrocardiogram-Language Models (ELMs)

Heart rate detection from ECG signals with clinical validation

Precision psychophysiology made easy

CardioLink is an app that provides cardiac telemonitoring for patients. This app allows doctors to see their patients recordings.

Develop an cheap Multimodal Cardiovascular Monitoring System for detecting PPG, PCG and ECG signal using MAX30102, INMP441 and AD8232 with STM32 ARM-Cortex MCU

Converting real-time EEG into sounds, music and visual effects

EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and developed at the SCCN/UCSD

Biosignal Processing in Python

This is the official repository for CardioLab. A machine and deep learning framework for the estimation and monitoring of laboratory abnormalities throught ECG data.

BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors

Chords is a web application that transforms your Arduino board into a powerful bio-potential signal acquisition tool, allowing you to visualize and record ECG, EMG, EOG, and EEG data directly in your browser.

The equivalent of EEG-to-MIDI, but for ECG.

Android Application for Real-Time ECG Anomaly Detection Written in Kotlin

Third year university IoT module for monitoring heart health in diabetic patients. The system combines hardware sensors, real-time data processing, and machine learning analytics to detect anomalies and track vital sign trends. The results are then displayed in a Streamlit web page.

MSYNC: Full-stack remote heart-monitoring platform combining Android, Spring Boot, React, and PyTorch. Collects real-time sensor data and detects ECG irregularities through a cloud-deployed ML model.

Factorization techniques for the analysis and separation of fetal ECG from maternal ECG for MSc Thesis in Numerical Methods for Computer Science @ Università degli Studi di Bari Aldo Moro, AY 2024/25