This toolbox offers 40 feature extraction methods (EMAV, EWL, MAV, WL, SSC, ZC, and etc.) for Electromyography (EMG) signals applications.
Simple Python interface to the Delsys wireless EMG system
A feature extraction toolbox for EMG signals written in MATLAB
A powerful toolbox for the analysis of HD-EMG recordings
A package for decomposing multi-channel EMG signals into individual motor unit activity.
Transcranial Magnetic Stimulation (TMS) Analysis Toolbox: A user friendly open source software for basic and advanced analysis of TMS related outcomes
A list of public EMG datasets and their papers, with a focus on raw EMG signals.
Myo armband electromyographic readings dataset for various wrist gestures.
Source code for multiple parameter modelling of synthetic electromyography data.
An open source library for analysis of respiratory EMG
DIY EMG VR Controller for Oculus Quest 2: low-cost, user-friendly electromyography-based control system with Arduino, MyoWare sensors, and 9gr servo motors. This beginner-oriented project offers a simple one-button setup to overcome input emulation limitations on Meta Quest and SteamVR devices, enabling virtual reality gaming for all #a11y
A Do It Yourself (DIY) Electromyography (EMG) shield for learning neauroscience with ease.
Studying facial muscle activation and their relationship with facial kinematics via facial landmarks. Utilizes an Arduino to generate a square wave with a specific duty cycle and frequency and synchronously trigger EMG and image acquisition.
Application collecting sEMG data from muscles has been written in C++ Signal feature extraction processing in Matlab
EMusicPulse utilizes electromyography technology to enable individuals, including those with disabilities, to create music through muscle signals, promoting accessibility, inclusivity, and technological empowerment in music creation and rehabilitation.
Software package and ROS wrapper of Delsys wireless EMG interface
Analyze data from surface EMG sensors, accelerometer, and gyroscope to recognize several hand-motion patterns, which can then be associated with a specific pattern in the 3D printed prosthetic arm 💪🏼
Python, PyQt5, microcontroller & electrode setup to measure EMG signals and test closed-loop (prosthetic) sensory feedback.
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