This toolbox offers 40 feature extraction methods (EMAV, EWL, MAV, WL, SSC, ZC, and etc.) for Electromyography (EMG) signals applications.
A list of public EMG datasets and their papers, with a focus on raw EMG signals.
A powerful toolbox for the analysis of HDsEMG recordings
Simple Python interface to the Delsys wireless EMG system
A feature extraction toolbox for EMG signals written in MATLAB
A package for decomposing multi-channel EMG signals into individual motor unit activity.
Decomposition of Neurophysiological Time Series Signals with a Particle Swarm Optimised Independence Estimator
An open source library for analysis of respiratory EMG
Source code for multiple parameter modelling of synthetic electromyography data.
Myo armband machine learning EMG dataset of various hand gestures
A Do It Yourself (DIY) Electromyography (EMG) shield for learning neauroscience with ease.
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
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
Desktop tool for GPU-accelerated decomposition, review, and editing of high-density EMG recordings.
A flow matching framework for EMG generation
Model of Motor Network during Parkinson's Disease and Deep Brain Stimulation. The model simulates LFP, EMG and associated force signals from the motor system. A multivariable adaptive control strategy is implemented in the model to control two biomarkers of Parkinsonian tremor and motor impairment symptoms.
Public multichannel sEMG dataset for stroke rehabilitation research, including recordings from healthy participants and stroke patients for hand-gesture recognition, biomedical signal processing, machine learning, and rehabilitation robotics.
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.
To associate your repository with the electromyography topic, visit your repo's landing page and select "manage topics."