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Motor Imagery EEG signal Classification on DWT and Crosscorrelated signal features

Implemented and compared some of the prominently used classication algorithms and feature extraction techniques to classify a two class Motor imagery based EEG data with high accuracies. Identified a combination of algorithms that outperformed other procedures in effectively classifying the dataset.

Paper

The project was accepted as a conference paper at IEEE ICIIS, 2014.

Please find the conference submission for this project here.

Please find the presentation for this project here.

License

This project is licensed under the MIT License - see the LICENSE.md file for details