Pattern recognition–based control of myoelectric prostheses offers amputees a natural, intuitive way of controlling the increasing functionality of modern myoelectric prostheses. Although this approach to prosthesis control is certainly attractive, it is a significant departure from existing control methods. The transition from the more traditional methods of direct or proportional control to pattern recognition–based control presents a training challenge that will be unique to each amputee. In this article, we describe specific ways that a transradial amputee, prosthetist, and occupational therapist team can overcome these challenges by developing consistent and distinguishable muscle patterns. A central part of this process is the use of a computer-based pattern recognition training system with which an amputee can learn and improve pattern recognition skills throughout the process of prosthesis fitting and testing. We describe in detail the manner in which four transradial amputees trained to improve their pattern recognition–based control of a virtual prosthesis by focusing on building consistent, distinguishable muscle patterns. We also describe a three-phase framework for instruction and training: 1) initial demonstration and conceptual instruction, 2) in-clinic testing and initial training, and 3) at-home training.
MICHAEL A. POWELL, BS, is affiliated with the Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, Maryland.
NITISH V. THAKOR, PHD, is affiliated with the Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, Maryland, and the SINAPSE Institute, National University of Singapore, Singapore.
Disclosure: The authors declare no conflict of interest.
Funding: This study was supported by the US Army (M. Powell is an active duty Army officer whose graduate studies are funded by the US Army). Additional funding was provided by the by the General Omar N. Bradley Fellowship and the National Institutes of Health.
Copyright © 2012 American Academy of Orthotists and Prosthetists.
Correspondence to: Michael A. Powell, BS, 3400 N Charles St, JHU Department of Biomedical Engineering, Clark Hall 101, Baltimore, MD 21218; e-mail: email@example.com or firstname.lastname@example.org