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Detect

MATLAB toolbox for continuous event detection

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DETECT overview

DETECT is a MATLAB™ Toolbox for the detection and identification of events in long multi-channel time series. Given training data of the events of interest and a feature extraction technique, DETECT can be used to train a classification model and label continuous time series data. Our motivation for developing DETECT was primarily for the analysis of multi-channel electroencephalography (EEG) signals.

Requirements and installation

The requirements to run DETECT are:

To install

Sample data can be downloaded from our software page at

http://visual.cs.utsa.edu/software/detect

Documentation and sample code for all of our functions can be found at

http://visual.cs.utsa.edu/detect/documentation/help/.

For more information on the status of this project, please visit our project page at

http://visual.cs.utsa.edu/detect.

Users can report software problems and issues by visiting our Issue Tracker page located at

http://visual.cs.utsa.edu/software/detect/issues

Reference

Lawhern, V., Hairston, W.D., McDowell, K., Westerfield, M. and Robbins, K. (2012)
Detection and Classification of Subject-Generated Artifacts in EEG Signals using Autoregressive Models
Journal of Neuroscience Methods 208(2), 181-189.

Support or Contact

You can post an issue on https://github.com/VisLab/detect/issues.