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  1. Figure 5. Comparison of several commonly used classification techniques using conventional classification accuracy. Results represent (a) average over 11 classes of motion collected from 10 nondisabled subjects and (b) average over 7 classes of motion collected from 5 subjects with transradial amputation. ANN = artificial neural network, GMM = Gaussian mixture model, KNN = K nearest neighbor, LDA = linear discriminant analysis, MBC = multiple binary classifier, QDA = quadratic discriminant analysis, SVM = support vector machine. Scheme E, Englehart K. Electromyogram pattern recognition for control of powered upper-limb prostheses: State of the art and challenges for clinical use. J Rehabil Res Dev. 2011;48(6):643-60.DOI:10.1682/JRRD.2010.09.0177

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