DICIS EEGFMMI A dataset

The dataset was created for the Motor Imagery classification by using an EMOTIV EPOC+ headset, to control a hexapod robot. Four test subjects between 23 and 36 years old, were trained and supervised to collect signals during several experimental tasks lasting three seconds each. According to the given task, subjects were instructed to stay still during the capture and invited to imagine closing and opening the right or the left fist focused on a stimulus video. The stimulus video of the fist closing-opening movements was played on the screen according to the temporal task sequence. The total trial duration was established at 19 s, where 6 s were used for the related MI tasks: the left fist as Task 1 (3 s), and the right fist as Task 2 (3 s). The neutral or reference action is taken as the final pause (3 s) to have an equal number of samples per class. Therefore, the developed dataset consists of 2,400 trials performed by four subjects (600 trials from each subject), representing 2,400×19 s (12.67 hours) of data capture. For each session duration, only signals of 3 s corresponding to Task1 (left fist MI), 3 s toTask2 (right fist MI), and 3 s to neutral action have been gathered to build the dataset.
The Data folder contains EEG data corresponding to 4 subjects. Each subject folder contains 3 CSV files (one for each task). Each CSV file is organized as follows: the header contains the sensor names and the following lines contain the signals corresponding to 200 trials (each trial contains 384 samples); therefore, the total number of samples is 76,800 (384 x 200 = 76,800 samples).