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 HD-EMG 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.

Source code for multiple parameter modelling of synthetic electromyography data.

An open source library for analysis of respiratory EMG

Myo armband machine learning EMG dataset of various hand gestures

A toolbox for offline muscle activity onset/offset detection in multi-channel EMG data

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

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

Synchronous acquisition and analysis for sEMG-MMG. NI9205 and TCP/IP were used to collect data generated by Quspin and BioSemi.

Going Contactless with Electromyography sensor as part of Biomedical Instrumentation project.

No description provided.

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 💪🏼

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.

Python, PyQt5, microcontroller & electrode setup to measure EMG signals and test closed-loop (prosthetic) sensory feedback.

Electromyography / Signal Analysis Project

legacy repo for R package suite for psychophysiological data; see github.com/psyphr-dev

Public and open-source version of a 2018 project using the combination of transcranial magnetic stimulation (TMS) and electromyography (EMG) in order to produce motor maps of the motor cortex of the human brain and represent them on 2 and 3 dimensional forms of an MRI Brain image. This project, source code, and all else within is governed by the AGPL 3.0 license. All modifications, alterations, and reproductions of any part of this project are subject to the terms of the AGPL 3.0 license. For more information regarding the terms of the AGPL 3.0 license, the software, and project as a whole, refer to the README.md file found in the top level of the repository.

Fully digitizes the analog operation amplifier filtering chain for electromyography signals. This simulation is a proof of concept that an accurate envelope signal can be produced without needing physical anolog op-amp filters.

Principal Analysis on Hand movement Electromygraphy

Analysis of bioelectrical signals recorded in the Laboratory of Bioelectrical Signals.

NeuroMT: Neurodegenerative Monitoring and Therapy Device Using EMG and TENS

Sheffield Bionic's Arm Division's repo for current prototypes and research- working primarily on the code for intuitive and adaptable electromyographically controlled transhumeral prosthetic devices.