Journal
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
Volume 58, Issue 6, Pages 1698-1705Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TBME.2011.2113182
Keywords
Amputee; electromyogram (EMG); myoelectric; myoelectric signal; pattern recognition; prostheses
Categories
Funding
- Natural Sciences and Engineering Research Council [217354-10, 171368-08]
- National Institute of Health [5R01HD058000-03]
- Atlantic Innovation Fund
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Recent literature in pattern recognition-based myoelectric control has highlighted a disparity between classification accuracy and the usability of upper limb prostheses. This paper suggests that the conventionally defined classification accuracy may be idealistic and may not reflect true clinical performance. Herein, a novel myoelectric control system based on a selective multiclass one-versus-one classification scheme, capable of rejecting unknown data patterns, is introduced. This scheme is shown to outperform nine other popular classifiers when compared using conventional classification accuracy as well as a form of leave-one-out analysis that may be more representative of real prosthetic use. Additionally, the classification scheme allows for real-time, independent adjustment of individual class-pair boundaries making it flexible and intuitive for clinical use.
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