CPS: Synergy: Cyber-Enabled Repetitive Motions in Rehabilitation
Lead PI:
Hanz Richter
Co-PI:
Abstract
The project will produce breakthroughs in the science of human-machine interaction and will produce lasting impacts on exercise machine technologies. The proposed Cyber-Enabled Exercise Machines (CEEMs) adapt to their users, seeking to maximize the effectiveness of exercise while guaranteeing safety. CEEMs measure and process biomechanical variables and generate adjustments to its own resistance, and generate cues to be followed by the exerciser. CEEMs are reconfigurable by software, which permits a wide range of exercises with the same hardware. Two prototype machines will be field-tested with the student-athlete population and used to validate project goals. The prototypes will be a valuable instrument for dissemination and outreach, as well as for student engagement. The outcomes of this research have repercussions beyond athletic conditioning: the same foundations and methodologies can be followed to design machines for rehabilitation, exercise countermeasure devices for astronauts, and custom exercise devices for the elderly and persons with disabilities. Thus, the project has the potential to improve health of society members at various levels. This research will contribute to the foundations of cyber-physical system science in the following aspects: biomechanical modeling and real-time musculoskeletal state estimation; estimation theory and unscented H-infinity estimation; control theory and human-machine interaction dynamics, and micro-evolutionary optimization for real-time systems. The proposed Cyber-Enabled Exercise Machines (CEEMs) are highly reconfigurable devices which adapt to the user in pursuit of an optimization objective, namely maximal activation of target muscle groups. Machine adaptation occurs through port impedance modulation, and optimal cues are generated for the exerciser to follow. The goals of the project are threefold: i) development of foundational cyber-physical science and technology in the field of human-machine systems; ii) development of new approaches to modeling, design, control and optimization of advanced exercise machines, and iii) application of the above results to develop two custom-built CEEMs: a rowing ergometer and a 2-degree-of-freedom resistance machine.
Hanz Richter

Dr. Richter received his Bachelor of Science degree in Mechanical Engineering from the Catholic University of Peru in 1994 and the Master of Science and Doctor of Philosophy degrees in Mechanical Engineering from Oklahoma State University in 1997 and 2001, respectively. He received a National Research Council postdoctoral fellowship to conduct research at the NASA John C. Stennis Space Center in Mississippi between 2001 and 2004.  In 2004, he was appointed as an Assistant Professor in Mechanical Engineering at Cleveland State University, and was subsequently promoted to Associate Professor in 2010. His research interests include robust control, modeling and optimization with applications to aerospace, biomedical, robotic and mechatronic systems.

Performance Period: 10/01/2015 - 08/31/2020
Institution: Cleveland State University
Sponsor: National Science Foundation
Award Number: 1544702