Brain Signals Classification Based on Fuzzy Lattice Reasoning

Eleni Vrochidou, Chris Lytridis, Christos Bazinas, George A. Papakostas, Hiroaki Wagatsuma and Vassilis G. Kaburlasos
Additional contact information
Eleni Vrochidou: HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece
Chris Lytridis: HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece
Christos Bazinas: HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece
George A. Papakostas: HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece
Hiroaki Wagatsuma: Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Kitakyushu 808-0135, Japan
Vassilis G. Kaburlasos: HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece

Mathematics, 2021, vol. 9, issue 9, 1-16

Abstract: Cyber-Physical System (CPS) applications including human-robot interaction call for automated reasoning for rational decision-making. In the latter context, typically, audio-visual signals are employed. ?his work considers brain signals for emotion recognition towards an effective human-robot interaction. An ElectroEncephaloGraphy (EEG) signal here is represented by an Intervals’ Number (IN). An IN-based, optimizable parametric k Nearest Neighbor ( k NN) classifier scheme for decision-making by fuzzy lattice reasoning (FLR) is proposed, where the conventional distance between two points is replaced by a fuzzy order function ( ? ) for reasoning-by-analogy. A main advantage of the employment of INs is that no ad hoc feature extraction is required since an IN may represent all-order data statistics, the latter are the features considered implicitly. Four different fuzzy order functions are employed in this work. Experimental results demonstrate comparably the good performance of the proposed techniques.

Keywords: Cyber-Physical System (CPS); ElectroEncephaloGraphy (EEG); emotion recognition; Fuzzy Lattice Reasoning (FLR); human-robot interaction; Intervals’ Number (IN); kNN classifier (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2227-7390/9/9/1063/pdf (application/pdf)
https://www.mdpi.com/2227-7390/9/9/1063/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:9:y:2021:i:9:p:1063-:d:551082

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().