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Invited Lecture
Rehabilitation Robotics for the Lower Extremity - A Path for Success
Hermano Igo Krebs
Massachusetts Institute of Technology
United States

Brief Bio
Hermano Igo Krebs joined MIT’s Mechanical Engineering Department in 1997 where he is a Principal Research Scientist – Newman Laboratory for Biomechanics and Human Rehabilitation. He also holds an affiliate position as an Adjunct Professor at University of Maryland School of Medicine, Department of Neurology and the Division of Rehabilitative Medicine. He is one of the founders of Interactive Motion Technologies, a start-up developing robotics for rehabilitation and one of the pioneers of rehabilitation robotics. His goal is to revolutionize rehabilitation medicine by applying robotics to assist, enhance, and quantify rehabilitation. His efforts led to the American Heart Association to endorse in its 2010 guidelines for stroke care the use of robots for upper extremity rehabilitation. Similar endorsement was issued by the Veterans Administration later in that same year.


Robotic therapy is a flagship example of the benefits of human-robot collaboration. However the 2010 American Heart Association guidelines for stroke care only endorsed robotic therapy for the upper extremity (UE), and not for the lower extremity (LE). In 2010, the US Veterans Administration similarly endorsed robotic therapy for UE but not for LE: “recommendation is made against routinely providing the [LE] intervention… At least fair evidence was found that the intervention is ineffective …” This apparent immaturity of LE robotic therapy reflects the fact that, to date, knowledge of human motor control has not been applied to LE robotic therapy. Knowledge of human motor control, sensing, and cognition has matured to the point that a fundamental theory of walking is now within reach. Walking can be composed of elementary actions, specifically submovements, oscillations, and mechanical impedance. This talk will discuss a proposal for a competent model of walking based on these elementary actions and code it into adaptive controllers that will allow multiple robotic devices to target human-like walking and rehabilitation.