Northwestern Events Calendar


Dr. Levi Hargrove: Pattern Recognition Based Control of Bionic Arms and Legs.

When: Monday, July 29, 2019
12:00 PM - 1:00 PM  

Where: Shirley Ryan AbilityLab, 10th floor Conference A-B, 355 E. Erie, Chicago, IL 60611 map it

Audience: Faculty/Staff - Student - Public - Post Docs/Docs - Graduate Students

Contact: Andrea Domenighetti  

Group: Shirley Ryan AbilityLab Research Seminar Series

Category: Lectures & Meetings



Powered bionic limbs are incredibly sophisticated and hold tremendous potential to restore ability for those with limb difference. Proper control of these devices requires that they intuitively and reliably respond to the user intentions. Over the past decade we have developed algorithms that respond to user intent by using pattern recognition algorithms to analyze signals measured from the bionic limb (eg inertial measurement unit) or from the user (eg electromyographric signals). The algorithms learn from the user and operate in real-time. In this talk, Dr. Hargrove will describe the algorithms and present outcomes measured from transradial and transhumeral amputees controlling multi-degree of freedom bionic arms, and transfemoral amputees ambulating with a fully powered bionic leg.

Speaker Info:

Levi J. Hargrove, PhD, P.Eng, received his MScE and PhD in Electrical Engineering from the University of New Brunswick (2005, 2008). He is currently the Director of the Regenstein Center for Bionic Medicine at the Shirley Ryan AbilityLab and an Associate Professor in the Departments of Physical Medicine & Rehabilitation and the McCormick School of Engineering at Northwestern University. A major goal of his research is to develop clinically realizable myoelectric control systems that can be made available to persons with limb loss in the near future. His research addresses all levels of amputation and has been published in the Journal of the American Medical Association and the New England Journal of Medicine. Key projects include the development of advanced and adaptive control systems for prosthetic legs, improving control of robotic hand prostheses, and intramuscular EMG signal processing.

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