Delete data that is in the same part with EEG data, which is deleted during pre-processing. It is available in the previous script by getting the index of deleted epoch of EEG about hyperscanning2-redesign HOT 5 CLOSED

  # Create dictionary which contains indices to delete
        key_counter = 0
        labels_indices = {}
        for val in range(0, 15000, 125):
            idx_start = val
            idx_end = val + 125
            labels_indices.update({key_counter : [idx_start, idx_end]})
            key_counter += 1
            labels_indices_2_delete = []

def extract_experimental_data(
    path_2_csv_files: str,
    path_2_save_experimental_file: str,
    labelsequence_experiment: list,
    bad_files: list = [],
):
    """
    Extract experimental data from raw EEG file (*.csv) that was obtained from hyperscanning2-redesign experiment \n

    Arguments :
        - path_2_csv_files (str) : path to raw EEG file \n
        - path_2_save_experimental_file (str) : path to save extracted baseline file for each condition \n
        - labelsequence (int) : order of pre-defined label sequence \n
        - bad_files (list) (optional) : file name(s) of raw EEG data, e.g., EEG-S8.csv, that wants to be skipped to process

    Return :
        Extracted *.fif (MNE-Python) file for each condition of hand (finger pointing and tracking).
        There are 18 files in total for each participant.