Supervised and Dynamic Neuro-Fuzzy Systems to Classify Physiological Responses in Robot-Assisted Neurorehabilitation

Luis D Lledó, Francisco J Badesa, Miguel Almonacid, José M Cano-Izquierdo, José M Sabater-Navarro, Eduardo Fernández and Nicolás Garcia-Aracil

PLOS ONE, 2015, vol. 10, issue 5, 1-16

Abstract: This paper presents the application of an Adaptive Resonance Theory (ART) based on neural networks combined with Fuzzy Logic systems to classify physiological reactions of subjects performing robot-assisted rehabilitation therapies. First, the theoretical background of a neuro-fuzzy classifier called S-dFasArt is presented. Then, the methodology and experimental protocols to perform a robot-assisted neurorehabilitation task are described. Our results show that the combination of the dynamic nature of S-dFasArt classifier with a supervisory module are very robust and suggest that this methodology could be very useful to take into account emotional states in robot-assisted environments and help to enhance and better understand human-robot interactions.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0127777

DOI: 10.1371/journal.pone.0127777

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