Journal of Rehabilitation Research & Development (JRRD)

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Volume 48 Number 6, 2011
   Pages 619 — 628

Abstract —  Target Achievement Control Test: Evaluating real-time myoelectric pattern-recognition control of multifunctional upper-limb prostheses

Ann M. Simon, PhD;1* Levi J. Hargrove, PhD;1-2 Blair A. Lock, MS;1 Todd A. Kuiken, MD, PhD1-3

1Center for Bionic Medicine, Rehabilitation Institute of Chicago, Chicago, IL; 2Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, IL; 3Biomedical Engineering Department, Robert R. McCormick School of Engineering and Applied Science, Northwestern University, Evanston, IL

Abstract — Despite high classification accuracies (~95%) of myoelectric control systems based on pattern recognition, how well offline measures translate to real-time closed-loop control is unclear. Recently, a real-time virtual test analyzed how well subjects completed arm motions using a multiple-degree of freedom (DOF) classifier. Although this test provided real-time performance metrics, the required task was oversimplified: motion speeds were normalized and unintended movements were ignored. We included these considerations in a new, more challenging virtual test called the Target Achievement Control Test (TAC Test). Five subjects with transradial amputation attempted to move a virtual arm into a target posture using myoelectric pattern recognition, performing the test with various classifier (1- vs 3-DOF) and task complexities (one vs three required motions per posture). We found no significant difference in classification accuracy between the 1- and 3-DOF classifiers (97.2% +/- 2.0% and 94.1% +/- 3.1%, respectively; p = 0.14). Subjects completed 31% fewer trials in significantly more time using the 3-DOF classifier and took 3.6 +/- 0.8 times longer to reach a three-motion posture compared with a one-motion posture. These results highlight the need for closed-loop performance measures and demonstrate that the TAC Test is a useful and more challenging tool to test real-time pattern-recognition performance.

Key words: multifunctional prosthesis, myoelectric control, pattern recognition, performance test, proportional control, prosthesis, surface electromyography, transradial amputation, upper limb, virtual environment.


View HTML  ¦  View PDF  ¦  Contents Vol. 48, No. 6
This article and any supplementary material should be cited as follows:
Simon AM, Hargrove LJ, Lock BA, Kuiken TA. Target Achievement Control Test: Evaluating real-time myoelectric pattern recognition control of multifunctional upper-limb prostheses. J Rehabil Res Dev. 2011;48(6): 619-28.
DOI:10.1682/JRRD.2010.08.0149
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Last Reviewed or Updated  Monday, July 11, 2011 9:30 AM

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