Hello,
I am new to working with EEG data. I need to develop a deep learning model that can classify hand movements (5 movements)
The dataset that I have is from 10 participants containing each 15 runs or trials.
The 15 runs are further divided into rest, eye movement and attempted movement. Attempted movement being the attempted hand movement.
My questions are
- how do I process all the 10 participants and the 15 runs. should I concatenate all the runs and handle each participant individually or should I just aggregate all the data from all the subjects and trials into one large EEG file.?
- should I only focus on the attempted movement runs, and discard rest + eye movement trials?
Kindly awaiting your response.