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EMG Control of Powered Prostheses: State-of-the-Art and Clinical Challenges

Photo of Dr. Kevin Englehart

Dr. Kevin Englehart

Professor, Electrical and Computer Engineering, University of New Brunswick

Director, Institute of Biomedical Engineering, University of New Brunswick

August 4, 2017 13:00 - 14:30

Mackenzie Building Room 4359, Carleton University

Refreshments will be served.

Admission: Free


Artificial limbs have provided cosmetic and functional replacements for those with deficiencies due to congenital defect or traumatic injury for many years. The first electrically powered prostheses became available in the 1950's, which was a significant advance in usability. A further advance in functionality came in the 1960's, when the first control system using signals from remaining muscles was developed. This form of control, using the myoelectric signal, provides a user with a self-contained, autonomous means of controlling a powered prosthesis.

The past decade has seen the development of powered upper limbs that have dramatically improved speed and dexterity. The impact of these devices upon usability and enhanced function has been limited by the need for a better man-machine interface to impart user intent. This has motivated intense research in novel methods of accessing motor intent from the central nervous system, including cortical and peripheral nerve interfaces. These invasive approaches hold promise, but require solving considerable medical and technical challenges before they are viable solutions.

The most practical solution in the near future remains using the myoelectric signal. The adoption of targeted muscle reinnervation (TMR), a procedure in which the brachial nerves are transferred to residual muscles in an amputee, allows the restoration of absent neural pathways. Patients can then contract the reinnervated muscles by attempting to move their missing limb. TMR, when combined with advanced pattern recognition methods, can enable intuitive control of many degrees of freedom using the myoelectric signal from reinnervated sites. This is particularly advantageous in individuals with high-level amputation.

This seminar will describe the evolution of myoelectric control to its current state-of-the-art. This will be set in the context of major new initiatives in the field, including breakthroughs in medical science, signal processing, and robotics.


Kevin Englehart received his PhD in Electrical Engineering from the University of New Brunswick in 1998 and became a faculty member in Electrical and Computer Engineering. In 2001, he became the Associate Director of the Institute of Biomedical Engineering at UNB, and became its fourth Director in July 2013. He teaches courses in biomedical signal processing, statistical signal processing, and communication theory.

Dr. Englehart has more than 160 peer-reviewed publications, and has authored five book chapters in biomedical signal processing. His research has resulted in significant advances in the control of artificial limbs. He has consulted on many commercial R&D projects in aeronautics, speech recognition, defense systems, and neural engineering.

Dr. Englehart is a Fellow of the Canadian Academy of Engineering. He is a recipient of the New Brunswick Innovation Foundation 2014 Innovation Award, the Canadian Medical and Biological Engineering Society Outstanding Biomedical Engineering Award, and the Queen's Diamond Jubilee Medal.

Last updated July 6, 2017

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