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Conference Paper: EEG-based quality of teleoperator identification using emotional states model

TitleEEG-based quality of teleoperator identification using emotional states model
Authors
Issue Date2015
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000856
Citation
The 2015 IEEE International Conference on Robotics and Biomimetics (IEEE-ROBIO 2015), Zhuhai, China, 6-9 December 2015. In Conference Proceedings, 2015, p. 470-475 How to Cite?
AbstractFatigue recognition has been a point of interest in many fields including robotic teleoperation. In our previous work we developed a method for evaluating the fatigue state of teleoperator using Quality of teleoperator (QoT). QoT can be estimated based on Radial Basis Function (RBF) network with 5 QoT indicators as input variables namely, long term excitement, short term excitement, boredom, meditation, and frustration. In this paper a new approach is presented for measuring the QoT based on EEG signals which is composed of two stages. In the first stage the EEG signals is projected to the Pleasure, Arousal, and Dominance (PAD) emotional states model. The resulted three emotional states then projected to QoT single dimension scale in the second stage. The experimental results showed improvement in the cross validation error, reduced form 10.7891 to 9.6133, and the complexity of the model is reduced by minimizing the number of variables from five to three. The statistical analysis results show positive correlation between pleasure and dominance states with the QoT value (p<0.05) and insignificant correlation between arousal state and QoT value. © 2015 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/235008
ISBN

 

DC FieldValueLanguage
dc.contributor.authorAlfatlawi, M-
dc.contributor.authorJia, Y-
dc.contributor.authorXi, N-
dc.date.accessioned2016-10-14T13:50:41Z-
dc.date.available2016-10-14T13:50:41Z-
dc.date.issued2015-
dc.identifier.citationThe 2015 IEEE International Conference on Robotics and Biomimetics (IEEE-ROBIO 2015), Zhuhai, China, 6-9 December 2015. In Conference Proceedings, 2015, p. 470-475-
dc.identifier.isbn978-146739674-5-
dc.identifier.urihttp://hdl.handle.net/10722/235008-
dc.description.abstractFatigue recognition has been a point of interest in many fields including robotic teleoperation. In our previous work we developed a method for evaluating the fatigue state of teleoperator using Quality of teleoperator (QoT). QoT can be estimated based on Radial Basis Function (RBF) network with 5 QoT indicators as input variables namely, long term excitement, short term excitement, boredom, meditation, and frustration. In this paper a new approach is presented for measuring the QoT based on EEG signals which is composed of two stages. In the first stage the EEG signals is projected to the Pleasure, Arousal, and Dominance (PAD) emotional states model. The resulted three emotional states then projected to QoT single dimension scale in the second stage. The experimental results showed improvement in the cross validation error, reduced form 10.7891 to 9.6133, and the complexity of the model is reduced by minimizing the number of variables from five to three. The statistical analysis results show positive correlation between pleasure and dominance states with the QoT value (p<0.05) and insignificant correlation between arousal state and QoT value. © 2015 IEEE.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000856-
dc.relation.ispartofIEEE International Conference on Robotics and Biomimetics Proceedings-
dc.rightsIEEE International Conference on Robotics and Biomimetics Proceedings. Copyright © IEEE.-
dc.rights©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.titleEEG-based quality of teleoperator identification using emotional states model-
dc.typeConference_Paper-
dc.identifier.emailXi, N: xining@hku.hk-
dc.identifier.authorityXi, N=rp02044-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ROBIO.2015.7418812-
dc.identifier.scopuseid_2-s2.0-84964546366-
dc.identifier.hkuros269340-
dc.identifier.spage470-
dc.identifier.epage475-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 161019-

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