Artificial Intelligence in Rehabilitation Engineering.

Catalog description

Semester course; 3 lecture hours. 3 credits. Prerequisite: EGRB 215 . Enrollment is restricted to engineering majors or with permission of instructor. This course offers a comprehensive study and application of the cutting-edge field of applying artificial intelligence to rehabilitation engineering. Students will gain an understanding of the innovative ways AI is revolutionizing the design and delivery of rehabilitation and prediction of patient outcomes. The course covers fundamental concepts in both AI and rehabilitation engineering. Through lectures, hands-on projects and case studies, students gain practical experience in developing AI algorithms in specific applications including: markerless motion capture that utilizes cloud-based data and machine learning, classification of human movement intent, speech classification from neural signals, and machine learning to predict outcomes of brain stimulation. By the end of the course, students are equipped with the knowledge and skills to contribute to the ongoing advancement of AI in rehabilitation engineering and improve patient care in this vital field.