Evaluation of surface EMG-based recognition algorithms for decoding hand movements

Myoelectric pattern recognition (MPR) to decode limb movements is an important advancement regarding the control of powered prostheses. However, this technology is not yet in wide clinical use. Improvements in MPR could potentially increase the functionality of powered prostheses. To this purpose, o...

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Veröffentlicht in:	Medical & biological engineering & computing Jg. 58; H. 1; S. 83 - 100
Hauptverfasser:	Abbaspour, Sara, Lindén, Maria, Gholamhosseini, Hamid, Naber, Autumn, Ortiz-Catalan, Max
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2020 Springer Nature B.V
Schlagworte:	Accuracy Algorithms Biomedical and Life Sciences Biomedical Engineering and Bioengineering Biomedicine Classification Classification (of information) Classifiers Computer Applications controlled study Correlation coefficient Correlation coefficients Decoding Dimensionality reduction Discriminant analysis Electromyography Feature extraction hand movement Hands Hjorth parameters Human Physiology Imaging k nearest neighbor K-nearest neighbors Linear discriminant analysis Maximum likelihood estimation maximum likelihood method motion Motion estimation Motion perception Motion recognition Myoelectric pattern recognition Myoelectrically controlled prosthetics Myoelectricity Nearest neighbor search Original Original Article Pattern recognition Prostheses Prosthetics Radiology reaction time Recognition algorithm Response time Root Mean Square support vector machine Support vector machines waveform Waveforms Dimensionality reduction Feature extraction Electromyography Myoelectric pattern recognition Classification
ISSN:	0140-0118, 1741-0444, 1741-0444
Online-Zugang:	Volltext
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