VisualEEG is a MATLAB/GUIDE based toolbox which can be used for visual analysis of EEG/EMG/TMS data.
Currently visualEEG is being developed on OSX El Capitan, MATLAB version R2015b. Windows/Linux users can experience some problems with the GUI layout.
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Clone the git repository.
$ git clone --recursive https://github.com/GallVp/visualEEG -
From MATLAB file explorer, add the folder/repository visualEEG to
pathby selecting the Selected folders and subfolders option. RunvisualEEG.mfile.
visualEEG can only import data saved in .mat files. All the files should be stored in a single directory. Following naming scheme should be used for files.
subXX_sessYY.mat
There are three ways in which data can be imported.
- By epoch time
- By epoch event
- Signal mat files
In method 1, only epoch time and sampling rate are needed. In method 2, sampling rate, time before epoch event and time after epoch event are needed. In this case, each .mat file should also contain another vector variable for event information. This variable should be a vector whose length is equal to total number of epochs. By method 3, mat fies exported from CED Signal program can be imported.
Sample Data folder contains EEG data for two subjects with 4 sessions each. This data was recorded using Emotiv Epoc. Each session contains 25 to 35 trials. The sampling rate is 128 Hz. The EEG data variable name is EEGdata. The length of each trail/epoch is 14 seconds. This data can be imported in visualEEG using default settings and By epoch time import method.
This feature is optional. If channel naming is required, a .xls file should be placed in the data directory. This spreadsheet should have two columns. First column containing channel numbers, while the second column containing channel names.
I would be very thankful if you contributed to the project in one or all of these ways:
- Adding issues
- Participating in discussions about issues here on GitHub and on Gitter
- Improving the documentation
- Forking the project and implementing new operations
New operations can be implemented easily in visualEEG by carrying out three steps in eegOperations class.
- Adding the name of the operation to
AVAILABLE_OPERATIONSproperty. - Implementing user interaction dialog boxes in
askArgsfunction to acquire operation parameters. - Implementing the operation in
applyOperationfunction.