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CORRECTION article

Front. Comput. Neurosci., 29 November 2016
Volume 10 - 2016 | https://doi.org/10.3389/fncom.2016.00119
This article is part of the Research Topic Computation meets Emotional Systems: a synergistic approach View all 13 articles

Corrigendum: Method for Improving EEG Based Emotion Recognition by Combining It with Synchronized Biometric and Eye Tracking Technologies in a Non-invasive and Low Cost Way

This article is a correction to:

  1. Method for Improving EEG Based Emotion Recognition by Combining It with Synchronized Biometric and Eye Tracking Technologies in a Non-invasive and Low Cost Way

    1. Read original article
\r\nJuan-Miguel Lpez-GilJuan-Miguel López-Gil1Jordi Virgili-GomJordi Virgili-Gomá2Rosa GilRosa Gil2Teresa Guilera,Teresa Guilera3,4Iolanda Batalla,,Iolanda Batalla3,4,5Jorge Soler-Gonzlez,,Jorge Soler-González4,5,6Roberto García*Roberto García2*
  • 1Department of Computer Languages and Systems, University of the Basque Country, Vitoria-Gasteiz, Spain
  • 2Department of Computer Science and Industrial Engineering, Universitat de Lleida, Lleida, Spain
  • 3Psychiatry Service, Santa Maria University Hospital, Lleida, Spain
  • 4Biomedical Research Institute of Lleida, Lleida, Spain
  • 5Department of Medicine, Faculty of Medicine, Universitat de Lleida, Lleida, Spain
  • 6Institut Català de la Salut IDIAP, Barcelona, Spain

A corrigendum on
Method for Improving EEG Based Emotion Recognition by Combining It with Synchronized Biometric and Eye Tracking Technologies in a Non-invasive and Low Cost Way

by López-Gil, J.-M., Virgili-Gomá, J., Gil, R., and García, R. (2016). Front. Comput. Neurosci. 10:85. doi: 10.3389/fncom.2016.00085

Reason for Corrigendum:

Due to an oversight, there were errors in the list of authors, correspondence author, acknowledgments, and author's contributions. These things have been fixed in all respective sections, as agreed with the rest of the authors and the research topic editor. The authors would like to apologize for any inconvenience caused and this change does not affect the scientific conclusions of the article in any way. The original article has been updated.

Author Contributions

JL explored different ways for emotion recognition, including sources of data from different signal measurement devices. He also helped defining the experimental protocol and providing ways to appropriately analyse gathered data. JV performed the device calibration and synchronization, data collection and facilitated the study. RGil coordinated the analysis of gathered information. She has found ways to expand it to medical environments. RGarcía participated in the definition of the protocol and explored ways to improve it. TG, IB, and JS recruited the medicine students that participated in the study and dealt with the required authorization by the ethics committee of the Arnau de Vilanova University Hospital. They also obtained the images and videos used in the study and supervised the experiments.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

This work has been supported by the Basque Government (IT421-10 and IT722-13), the Gipuzkoa Council (FA-208/2014-B) and the University of the Basque Country (PPV12/09). It has also been supported by InDAGuS (Spanish Government TIN2012-37826-C02) and INSPIRES, the Polytechnic Institute of Research and Innovation in Sustainability, Universitat de Lleida, Spain. We would also like to acknowledge the support of the International Affective Picture System (IAPS) and Simon Baron-Cohen who provided, respectively, the images and videos used during the experiment. And the Universitat de Lleida medicine students for their participation.

Keywords: emotions, EEG, eye tracking, biometric information, empathy

Citation: López-Gil J-M, Virgili-Gomá J, Gil R, Guilera T, Batalla I, Soler-González J and García R (2016) Corrigendum: Method for Improving EEG Based Emotion Recognition by Combining It with Synchronized Biometric and Eye Tracking Technologies in a Non-invasive and Low Cost Way. Front. Comput. Neurosci. 10:119. doi: 10.3389/fncom.2016.00119

Received: 14 September 2016; Accepted: 08 November 2016;
Published: 29 November 2016.

Edited by:

Jose Manuel Ferrandez, Universidad Politécnica de Cartagena, Spain

Reviewed by:

Juan Manuel Gorriz, University of Granada, Spain
Antonio Fernández-Caballero, University of Castilla–La Mancha, Spain

Copyright © 2016 López-Gil, Virgili-Gomá, Gil, Guilera, Batalla, Soler-González and García. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Roberto García, cmdhcmNpYUBkaWVpLnVkbC5jYXQ=

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