Towards limb position invariant myoelectric pattern recognition using time-dependent spectral features

Recent studies in Electromyogram (EMG) pattern recognition reveal a gap between research findings and a viable clinical implementation of myoelectric control strategies. One of the important factors contributing to the limited performance of such controllers in practice is the variation in the limb...

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Vydáno v:	Neural networks Ročník 55; s. 42 - 58
Hlavní autoři:	Khushaba, Rami N., Takruri, Maen, Miro, Jaime Valls, Kodagoda, Sarath
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Kidlington Elsevier Ltd 01.07.2014 Elsevier
Témata:	Adult Applied sciences Artificial Limbs Biological and medical sciences Computer science; control theory; systems Data processing. List processing. Character string processing Electrodiagnosis. Electric activity recording Electromyogram (EMG) Electromyography - methods Exact sciences and technology Feature extraction Female Humans Invariants Investigative techniques, diagnostic techniques (general aspects) Limbs Male Medical sciences Memory organisation. Data processing Movement - physiology Movements Myoelectric control Pattern recognition Pattern Recognition, Automated - methods Posture - physiology Segments Signal processing Signal Processing, Computer-Assisted Software Spectra Spectral moments Time Factors User-Computer Interface Young Adult Electromyogram (EMG) Signal processing Spectral moments Invariant Correlation Fourier transformation Prosthesis Irregularity Video signal Modeling Time dependence Signal spectrum Classification Size effect Selection criterion Electromyography Medical application Pattern extraction Video technique Pattern recognition Real time Time domain method Feature extraction Data gathering Power spectrum
ISSN:	0893-6080, 1879-2782, 1879-2782
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