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Critical Reviews™ in Biomedical Engineering
SJR: 0.207 SNIP: 0.376 CiteScore™: 0.79

ISSN Imprimir: 0278-940X
ISSN On-line: 1943-619X

Volumes:
Volume 47, 2019 Volume 46, 2018 Volume 45, 2017 Volume 44, 2016 Volume 43, 2015 Volume 42, 2014 Volume 41, 2013 Volume 40, 2012 Volume 39, 2011 Volume 38, 2010 Volume 37, 2009 Volume 36, 2008 Volume 35, 2007 Volume 34, 2006 Volume 33, 2005 Volume 32, 2004 Volume 31, 2003 Volume 30, 2002 Volume 29, 2001 Volume 28, 2000 Volume 27, 1999 Volume 26, 1998 Volume 25, 1997 Volume 24, 1996 Volume 23, 1995

Critical Reviews™ in Biomedical Engineering

DOI: 10.1615/CritRevBiomedEng.v38.i4.30
pages 381-391

Myoelectric Control in Neurorehabilitation

Ning Jiang
Department of Neurorehabilitation Engineering, Bernstein Center for Computational Neuroscience, Georg- August University of Göttingen, Göttingen and Strategic Technology Management, Otto Bock Healthcare GmbH, Duderstadt, Germany
Deborah Falla
Dept.of Neurorehabilitation Engineering,Bernstein Center for Computational Neuroscience,Georg- August University of Göttingen, Germany; and Center for Sensory-Motor Interaction, Department of Health Science and Technology,Aalborg University, Denmark
Andrea d'Avella
Department of Neuromotor Physiology, Santa Lucia Foundation, Rome, Italy
Bernhard Graimann
Strategic Technology Management, Otto Bock Healthcare GmbH, Duderstadt, Germany
Dario Farina
Department of Bioengineering, Imperial College London, Royal School of Mines, London SW7 2AZ

RESUMO

A myoelectric signal, or electromyogram (EMG), is the electrical manifestation of a muscle contraction. Through advanced signal processing techniques, information on the neural control of muscles can be extracted from the EMG, and the state of the neuromuscular system can be inferred. Because of its easy accessibility and relatively high signal-to-noise ratio, EMG has been applied as a control signal in several neurorehabilitation devices and applications, such as multi-function prostheses and orthoses, rehabilitation robots, and functional electrical stimulation/therapy. These EMG-based neurorehabilitation modules, which constitute muscle-machine interfaces, are applied for replacement, restoration, or modulation of lost or impaired function in research and clinical settings. The purpose of this review is to discuss the assumptions of EMG-based control and its applications in neurorehabilitation.