Classification of Electroencephalogram Signal for Developing Brain-Computer Interface Using Bioinspired Machine Learning Approach

Algorithm 1

AR Yule-Walker method-based extraction.

The feature extraction algorithm mentioned previously consists of subsequent steps:
	Step 1: Collect sample data (S) of two-channel EEG signals for 5 seconds.
Step 2: S was divided into 0.1-second windows.
Step 3: Bandpass filters were applied to extract 22 frequency bands from S.
Step 4: Apply the AR Yule method to the frequency band signal to extract the AR coefficients and then obtain PSD features using equation (1). Model order p is fixed as 4.
Step 5: Replicate steps 1 to 4 for each trial for all tasks.
Step 6: 22 features were picked for every task per trial and repeat the same process for ten trials for four tasks.
Step 7: 40 (4 tasks x 10 trials = 40) data samples for one subject were obtained to train and test the optimized neural network classifier.
Step 8: Do steps 1 to 7 for twenty subjects to gather a master dataset.