Flexible Control of Paralyzed Human Arms with Machine Learning

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Date/Time
Date(s) - 11/13/2015
3:00 pm - 5:00 pm

Location
CSU - Fenn Hall 103

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The IEEE Cleveland Section, IEEE Control Systems Society Cleveland Chapter, and the HKN Epsilon Alpha Chapter at Cleveland State University jointly present:

Flexible Control of Paralyzed Human Arms with Machine Learning

by Dr. Eric Schearer

Agenda
3:00-3:30: social hour
3:30-4:30: seminar
4:30-5:00: Q&A

Who is invited?
Anyone interested in attending
Priority will be given to members of IEEE.

CPD
One credit available
Bring your flyer for credit

Refreshment and soft drink will be provided!

RSVP: Dr. Lili Dong • L.Dong34@csuohio.edu • 216-687-5312

Abstract of the seminar: Functional Electrical Stimulation (FES) is a promising technology for restoring lost function to people with high spinal cord injuries. Controlling a paralyzed human arm with FES is a daunting task because the neuromuscular system is complex and constantly changing, and the tasks performed by the arm are varied and performed in a dynamic environment. Machine learning has begun to show promise in solving some of these flexible control problems for robots. This presentation focuses on the use of machine learning for flexible control of paralyzed human arms.

Dr. Eric Schearer is an Assistant Professor of Mechanical Engineering (ME) at Cleveland State University (CSU). He earned a B.S. in ME from the University of Notre Dame, an M.S. in Robotics from Carnegie Mellon University, and a Ph.D. in ME from Northwestern University. He served as an Air Force officer and worked as a consultant before he joined CSU.

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