This toolbox offers 40 feature extraction methods (EMAV, EWL, MAV, WL, SSC, ZC, and etc.) for Electromyography (EMG) signals applications.
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Updated
Jan 11, 2021 - MATLAB
This toolbox offers 40 feature extraction methods (EMAV, EWL, MAV, WL, SSC, ZC, and etc.) for Electromyography (EMG) signals applications.
A feature extraction toolbox for EMG signals written in MATLAB
This repository contains a set of Matlab scripts to process EEG and EMG signals (feature extraction, spectral analysis, ...).
Essential Motor Cortex Signal Processing MATLAB Toolbox which implements various methods for three major aspects of investigating human motor cortex from Neuroscience view point: (1) ERP estimation and quantification, (2) Cortical Functional Connectivity analysis and (3) EMG quantification
Algorithms and evaluation toolkit for removing strong cardiac interference from surface EMG measurements
An improved multiscale sample entropy algorithm to extract signal features: "Analysis of fatigue in the biceps brachii by using rapid refined composite multiscale sample entropy"
Code to analyze high-density EEG and concurrent EMG/EOG datastreams during balance perturbations (replicates results from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6088363/)
Using 2D and 3D AUC diagrams we provide improved detection accuracy of Parkinson's disease
The objective of our project is to use electromyography (EMG) in order to classify different hand gestures. EMG is a technique for evaluating and recording the electrical activity produced skeletal muscles. We used double channel surface electrodes to record EMG, with 3 electrodes per channel, one for ground and 2 for the differential input. We …
Selecting the best time-domain EMG features using the novel and some classical feature selection algorithms.
The aim of this project was to train a LDA and SVM classifier in MATLAB and compare their performance to determine which is more ideal to be used in online training
Real-time EMG signal classification for the bionic prosthesis design
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