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

ISSN Druckformat: 0278-940X
ISSN Online: 1943-619X

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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


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.