EE440: Brain-Machine Learning
This course develops the concepts from machine learning, signal processing, and neuroscience required to understand how modern brain-machine interfaces - technologies that interact with the nervous system for therapeutic or rehabilitative purposes - interpret and respond to brain signals. Examples of these technologies include retinal prostheses for the blind and brain-driven limb prostheses for amputees. The course also examines brain-machine interfaces at the system level through directed readings of the scientific and engineering literature. Specific course topics include basic neuroanatomy and neurophysiology for engineers and statistical techniques for the dimensionality reduction, de-noising, classification, and clustering of neural signals.
Course Information
- Syllabus
- Policy
- Student Presentation Schedule
- Student Presentation Rubric
- IEEE Code of Ethics
