Principal Components Analysis Preprocessing for Improved Classification Accuracies in Pattern-Recognition-Based Myoelectric Control

Information extracted from multiple channels of the surface myoelectric signal (MES) recording sites can be used as inputs to control systems for powered upper limb prostheses. For small, closely spaced muscles, such as the muscles in the forearm, the detected MES often contains contributions from m...

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Veröffentlicht in:	IEEE transactions on biomedical engineering Jg. 56; H. 5; S. 1407 - 1414
Hauptverfasser:	Hargrove, Levi J., Li, Guanglin, Englehart, Kevin B., Hudgins, Bernard S.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.05.2009 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Amputee Amputees Conductors Control systems Data mining Decorrelation Dispersion electromyography (EMG) Electromyography - methods Forearm - physiology Humans Muscle Contraction - physiology Muscle, Skeletal - physiology Muscles myoelectric myoelectric signal (MES) Pattern recognition Pattern Recognition, Automated - methods Principal Component Analysis Principal components analysis prostheses Prosthetics Rotation measurement Signal Processing, Computer-Assisted tranrsradial
ISSN:	0018-9294, 1558-2531, 1558-2531
Online-Zugang:	Volltext
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