Motor Imagery Classification with EEG

In my final project, I developed a pipeline for classifying motor imagery tasks using EEG data. I extracted relevant features, applied dimensionality reduction with PCA, and trained a Linear Discriminant Analysis classifier. The results demonstrated that this approach could successfully distinguish between different imagined movements, though performance varied depending on feature selection.
I concluded that combining feature extraction with dimensionality reduction is an effective strategy for EEG‑based brain–computer interface applications.