Brain Interface Machine for post-stroke rehabilitation

Brain Machine Interfaces (MCIs) allow the use of the brain signal for compensate for a lost function by giving paralyzed people the opportunity to drive a device, a computer or a robot.

The purpose of this study is to improve the EEG signal classification (LDA, PCA) in order to better detect the patient’s intent to move during his rehabilitation of his hand. This project was made with Jules HACQUARD and tutored by Gérard DRAY

Environment

• Matlab
• EEGLab