Current state of digital signal processing in myoelectric interfaces and related applications

•Critical issues and practices for myoelectric interfaces are discussed.•Robust classification in real use is the main challenge of sEMG interfaces.•Expected trend is toward regression and factorization methods and sensor fusion.•Simplified sEMG setup may be adequate in real-life environment.•Potent...

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Bibliographic Details
Published in:Biomedical signal processing and control 2015-04, Vol.18, p.334-359
Main Authors: Hakonen, Maria, Piitulainen, Harri, Visala, Arto
Format: Article
Language:English
Subjects:
Classification
Feature extraction
Myoelectric interface
Pattern recognition
Surface electromyography
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Summary:•Critical issues and practices for myoelectric interfaces are discussed.•Robust classification in real use is the main challenge of sEMG interfaces.•Expected trend is toward regression and factorization methods and sensor fusion.•Simplified sEMG setup may be adequate in real-life environment.•Potential uses of sEMG interfaces are rapidly increasing. This review discusses the critical issues and recommended practices from the perspective of myoelectric interfaces. The major benefits and challenges of myoelectric interfaces are evaluated. The article aims to fill gaps left by previous reviews and identify avenues for future research. Recommendations are given, for example, for electrode placement, sampling rate, segmentation, and classifiers. Four groups of applications where myoelectric interfaces have been adopted are identified: assistive technology, rehabilitation technology, input devices, and silent speech interfaces. The state-of-the-art applications in each of these groups are presented.
ISSN:1746-8094
DOI:10.1016/j.bspc.2015.02.009