title: A decision-based velocity ramp for minimizing the effect of misclassifications during real-time pattern recognition control.
abstract: Real-time pattern recognition control is frequently affected by misclassifications. This study investigated the use of a decision-based velocity ramp that attenuated movement speed after a change in classifier decision. The goal was to improve prosthesis positioning by minimizing the effect of unintended movements. Non-amputee and amputee subjects controlled a prosthesis in real-time using pattern recognition. While performing a target achievement test in a virtual environment, subjects had a significantly higher completion rate (p < 0.05) and a more direct path (p < 0.05) to the target with the velocity ramp than without it. Using a physical prosthesis, subjects stacked a greater average number of 1 cubes (p < 0.05) in three minutes with the velocity ramp than without it (76% more blocks for non-amputees; 89% more blocks for amputees). Real-time control using the velocity ramp also showed significant performance improvements above using majority vote. Eighty-three percent of subjects preferred to control the prosthesis using the velocity ramp. These results suggest that using a decision-based velocity ramp with pattern recognition may improve user performance. Since the velocity ramp is a post-processing step, it has the potential to be used with a variety of classifiers for many applications.
authors: Ann M
authors: AM
authors: Simon
authors: Levi J
authors: LJ
authors: Hargrove
authors: Blair A
authors: BA
authors: Lock
authors: Todd A
authors: TA
authors: Kuiken
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