/Alpha-Rhythm-Feature-Selection

Selection of relevant features for classification of open and closed eyes

Primary LanguagePython

Selection of relevant features for alpha rhythm classification

In this work, we implement a feature selection technique utilizing $R^2$ feature maps to identify the most significant frequencies and channels used for classification of alpha rhythms. Our methodology was applied to data from a subject in the EEG MMIDB database, the resulting $R^2$ map is visualized and analysed. We show that the most informative set of frequencies lie around the frequency of $9.9$Hz in the visual cortex of the brain.

For more detail please read: Alpha rhythm feature selection

Setup

In order to run the program user must do the following:

  1. Create a virtual environment:

    python3 -m venv venv

  2. Activate virtual environment:

    . venv/bin/activate

  3. Install dependencies:

    pip install -r requirements.txt

Usage

You can run the code using:

python3 main.py <subject>.

e.g python3 main.py S001