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Enhancing Classification Accuracy With Added Channels for Myoelectric Signals

This study explores the impact of adding channels on classification accuracy in surface and intramuscular myoelectric signal classification. By comparing optimal and symmetrical channel subsets, the research sheds light on improving pattern recognition for controlling powered upper-limb prostheses.

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Enhancing Classification Accuracy With Added Channels for Myoelectric Signals

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  1. Figure 2. Increase in classification accuracy as channels are added for both optimal and symmetrical channel subsets. Source: Reprinted with per-mission of IEEE from Hargrove LJ, Englehart K, Hudgins B. A comparison of surface and intramuscular myoelectric signal classification. IEEE Trans Biomed Eng. 2007;54(5):847–53.[PMID: 17518281]DOI:10.1109/TBME.2006.889192 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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