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Real and imaginary motion classification based on rough set analysis of EEG signals for multimedia applications

Abstract

Rough set-based approach to the classification of EEG signals of real and imaginary motion is presented. The pre-processing and signal parametrization procedures are described, the rough set theory is briefly introduced, and several classification scenarios and parameters selection methods are proposed. Classification results are provided and discussed with their potential utilization for multimedia applications controlled by the motion intent. Accuracy metrics of classification for real and imaginary motion obtained with different parameter sets are compared. Results of experiments employing recorded EEG signals are commented and further research directions are proposed.

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Category:
Articles
Type:
artykuł w czasopiśmie wyróżnionym w JCR
Published in:
MULTIMEDIA TOOLS AND APPLICATIONS no. 76, pages 25697 - 25711,
ISSN: 1380-7501
Language:
English
Publication year:
2017
Bibliographic description:
Szczuko P.: Real and imaginary motion classification based on rough set analysis of EEG signals for multimedia applications// MULTIMEDIA TOOLS AND APPLICATIONS. -Vol. 76, (2017), s.25697-25711
DOI:
Digital Object Identifier (open in new tab) 10.1007/s11042-017-4458-7
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