NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing

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

Weasis is a DICOM viewer available as a desktop application or as a web-based application.

Native Python WFDB package

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

A unified multi-task time series model.

Open source ECG holter

A Python Toolbox for Statistics and Neurophysiological Signal Processing (EEG, EDA, ECG, EMG...).

Scripts and modules for training and testing neural network for ECG automatic classification. Companion code to the paper "Automatic diagnosis of the 12-lead ECG using a deep neural network".

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

ECG arrhythmia classification using a 2-D convolutional neural network

BioAmp EXG Pill is a small and elegant Analog Front End (AFE) board for BioPotential signal acquisition.

ECG classification programs based on ML/DL methods

A Collection Python EEG (+ ECG) Analysis Utilities for OpenBCI and Muse

ECG classification using MIT-BIH data, a deep CNN learning implementation of Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network, https://www.nature.com/articles/s41591-018-0268-3 and also deploy the trained model to a web app using Flask, introduced at

Deep learning ECG models implemented using PyTorch

Inter- and intra- patient ECG heartbeat classification for arrhythmia detection: a sequence to sequence deep learning approach

Interactive Brain Playground - Browser based tutorials on EEG with webbluetooth and muse

The programming interface for your body and mind

ECG classification from short single lead segments (Computing in Cardiology Challenge 2017 entry)