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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
- Verified by:
- Gdańsk University of Technology
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