Artificial Intelligence in BCI for Neurorehabilitation

This overview delves into AI-driven Brain-Computer Interfaces (BCIs) in neurorehabilitation, highlighting mechanisms like EEG signal processing and feedback loops to enable motor recovery. It covers AI advancements such as deep learning and adaptive systems, explores practical clinical implementations, portable designs, and improved therapy access. Challenges include reliability of signals, data limitations, and calibration delays. Ethical concerns like privacy safeguards and transparency are...