I’m trying to replicate the train/test split method described in the paper: *"Investigating Critical Frequency Bands and Channels for EEG-Based Emotion Recognition with Deep Neural Networks" (Zheng & Lu, 2015) *.

The paper states:

*"We collected EEG data from 15 subjects, with each subject performing the experiment twice (two sessions) at one-week intervals. There are 30 experiments evaluated in total. The training data and test data come from different sessions of the same experiment. The training set contains nine sessions, while the test set contains six sessions from the same experiment."*

My Dataset Structure:

• 15 subjects
• Each subject has 3 sessions (not 2 as in the paper)
• Each session contains 15 trials (EEG recordings) → 45 trials per subject total

My Interpretation: Since the paper mentions 9 training sessions and 6 test sessions but each subject only has 2 sessions (in their case), I’m confused about how to apply this split.

Possible Approach (Need Validation):

OR

Key Questions:

Has anyone implemented this split before or understands how to align it with a dataset structured like mine? Any insights would be greatly appreciated!