Motion imagery detection from EEG data using deep learning for lower-limb exoskeleton control

Research plan:

1. Study MI EEG principles, BCI applications, and lower-limb exoskeleton control.

2. Analyze existing EEG measurement protocols and datasets, identifying challenges.

3. Design an EEG acquisition process conducted at the department, expand the dataset, and preprocess signals. Additionally, replicate the experiment in the laboratory with at least three other participants.

4. Develop and optimize an advanced deep learning model for motion detection from EEG data.

5. Compare the motion detection results from EEG data obtained using the original and expanded data collections.

6. Evaluate the achieved results.