I’m new to EEG signal analysis and I’m working with a dataset of .set files from 32 subjects. I’ve managed to extract epochs and compute frequency-based features (delta, theta, alpha, beta, gamma), but only for one subject so far. I’m not sure how to concatenate the features from all subjects into a single array to use them as input for a model like Random Forest. Also, is it normal to end up with a large number of features (around 1120 in my case)?
If you are extracted all features and labels corresponding to each subject. Then you can append features (all the lists of features of each subject) and same for labels. After that you can use this for model tanning “X = np.concatenate(all_features, axis=0) and
y = np.concatenate(all_labels, axis=0)”. If its not work then share all your .set file, i will review and find my best solution.
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