Assessment of the users emotions in haptic feedback tasks using the Emotiv Insight device

dc.creatorCorredor Camargo, Javier Adolfo
dc.creatorPeña Cortes, Cesar Augusto
dc.creatorPardo Garcia, Aldo
dc.date2019-11-12T15:20:50Z
dc.date2019-11-12T15:20:50Z
dc.date2019-03-01
dc.date.accessioned2023-10-03T19:59:03Z
dc.date.available2023-10-03T19:59:03Z
dc.identifierJ. Corredor, C. Peña, A. Pardo, “Evaluación de las emociones de usuarios en tareas con realimentación háptica utilizado el dispositivo Emotiv Insight,” INGE CUC, vol. 15, no. 1, pp. 9-16, 2019. DOI: http://doi.org/10.17981/ingecuc.15.1.2019.01
dc.identifierhttp://hdl.handle.net/11323/5595
dc.identifierhttps://doi.org/10.17981/ingecuc.15.1.2019.01
dc.identifier10.17981/ingecuc.15.1.2019.01
dc.identifier2382-4700
dc.identifierCorporación Universidad de la Costa
dc.identifier0122-6517
dc.identifierREDICUC - Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9173575
dc.descriptionIntroduction− This study assesses the five-performance metrics, available on the Emotive Insight device in a virtual toolpath tracking task through a mobile robot. Objective− Characterize and/or determine if some EEG metrics are related to primitives of a teleoperation task, where haptic feedback is provided, in order to verify if it can be useful to incorporate the information available from the Emotiv device in a shared control strategy. Methodology− An experimental design was formulated, which includes the recording and analysis of neurosigns in five users with a Brain Computer Interface (BCI), executing tasks of teleoperation of a mobile robot in the Environment of VREP (Virtual Robot Experimentation Platform). Results− The results show that engagement and relaxation are emotions that could be useful to identify demanding situations in tracking path and evasion of obstacles such as the experimental setup proposed in this article. On the other hand, it is observed that some metrics such as stress, excitement, interest and focus, on average, remain at similar levels during the task execution. Conclusions− Including brain computer interfaces of low-cost, such as the Emotiv in tasks with haptic feedback, offers new possibilities for assessment user performance and potential for control applications.
dc.descriptionIntroducción: Este estudio evalúa las cinco métricas de desempeño, disponibles en el dispositivo Emotiv Insight en una tarea virtual de seguimiento de trayectorias por medio de un robot móvil. Objetivo: Caracterizar y/o determinar si algunas métricas EEG se relacionan con primitivas de una tarea de tele operación, donde se realimentan señales hápticas, en pro de verificar si puede ser útil incorporar la información disponible del dispositivo Emotiv en una estrategia de control compartido. Metodología: Se formuló un diseño experimental, que incluye el registro y análisis de neuroseñales en cinco usuarios con una Interfaz Cerebro Computador (ICC), ejecutando tareas de teleoperación de un robot móvil en el entorno de VREP (Virtual Robot Experimentation Platform). Resultados: Los resultados muestran que el compromiso y la relajación son emociones que podrían ser de utilidad para identificar situaciones demandantes en tareas de seguimiento y evasión de obstáculos. Por otro lado, se observa que algunas métricas como estrés, excitación, interés y enfoque, en promedio, se mantienen en niveles similares durante la ejecución de la tarea. Conclusiones: Incluir interfaces cerebro computador de bajo costo, como el Emotiv en tareas con realimentación háptica, ofrece nuevas posibilidades para la evaluación del desempeño del usuario y potencialmente para control.
dc.format8 páginas
dc.formatapplication/pdf
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dc.languagespa
dc.publisherCorporación Universidad de la Costa
dc.relationINGE CUC; Vol. 15, Núm. 1 (2019)
dc.relationINGE CUC
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dc.relationC. Passenberg, A. Glaser, and A. Peer, “Exploring the Design Space of Haptic Assistants: The Assistance Policy Module”, IEEE Transactions on Haptics, vol. 6, no. 4, pp. 440-452, Oct. 2013. [Online]. https://doi.org/10.1109/TOH.2013.34
dc.relationK. Holewa and A. Nawrocka, “Emotiv EPOC neuroheadset in brain-computer interface”, Proceedings of the 2014 15th International Carpathian Control Conference (ICCC). pp. 149–152, May. 2014. https://doi.org/10.1109/CarpathianCC.2014.6843587
dc.relationG. S. Taylor and C. Schmidt, “Empirical Evaluation of the Emotiv EPOC BCI Headset for the Detection of Mental Actions”, Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 56, no. 1, pp. 193–197, Sep. 2012. https://doi.org/10.1177/1071181312561017
dc.relationR. Lievesley, M. Wozencroft and D. Ewins, “The Emotiv EPOC neuroheadset: an inexpensive method of controlling assistive technologies using facial expressions and thoughts?”, Journal of Assistive Technologies, vol. 5, no. 2, pp. 67–82, Jun. 2011. https://doi.org/10.1108/17549451111149278
dc.relationR. Maskeliunas, R. Damasevicius, Martisius and M. Vasiljevas,“Consumer-grade EEG devices: are they usable for control tasks?,PeerJ 4, e1746, Mar. 2016. https://doi.org/10.7717/peerj.1746
dc.relationC.-L. Lin, F.-Z. Shaw, K.-Y. Young, C.-T. Lin and T.-P. Jung,“EEG correlates of haptic feedback in a visuomotor tracking task”, NeuroImage, vol. 60, no. 4, pp. 2258–2273, May. 2012. https://doi.org/10.1016/j.neuroimage.2012.02.008
dc.relationM. Grunwald, T. Weiss, W. Krause, L. Beyer, R. Rost, I. Gutberlet and H.-J. Gertz, “Power of theta waves in the EEG of human subjects increases during recall of haptic information”, Neuroscience Letters, vol. 260, no. 3, pp. 189–192, Feb. 1999. https://doi.org/10.1016/S0304-3940(98)00990-2
dc.relationH. Miura, J. Kimura, N. Matsuda, M. Soga and H, Taki, “Classification of Haptic Tasks based on Electroencephalogram Frequency Analysis”, Procedia Computer Science, vol. 35, Supplement (C), pp. 1270–1277, Jan. 2014. https://doi.org/10.1016/j.procs.2014.08.226
dc.relationW. Jia, Y. Luo, Y. Hu and J. Zhang, “Adaptive Force Control Tasks Have Far-Transfer Effect on Sustained Attention”, 9th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), vol. 2, pp. 212–217. Aug. 2017. https://doi.org/10.1109/IHMSC.2017.162
dc.relationT. Palomaki, “EEG-based brain-computer interface with visual and haptic feedback”, Master’s thesis, Helsinki University of Technology, 2007. Available: http://lib.tkk.fi/Dipl/2007/urn007655.pdf
dc.relationA. Chatterjee, V. Aggarwal, A. Ramos, S. Acharya, N. V. Thakor, “Operation of a Brain-Computer Interface Using Vibrotactile Biofeedback”, 3rd International IEEE/EMBS Conference on Neural Engineering. pp. 171–174, May. 2007. https://doi.org/10.1109/CNE.2007.369639
dc.relationL. George, M. Marchal, L. Glondu and A. Lecuyer, “Combining Brain-Computer Interfaces and Haptics: Detecting Mental Workload to Adapt Haptic Assistance”, Haptics: Perception, Devices, Mobility, and Communication. Springer, Berlin, Heidelberg, pp. 124–135, Jun. 2012. https://doi.org/10.1007/978-3-642-31401-8_12
dc.relationM. A. Benloucif, C. Sentouh, J. Floris, P. Simon and J. C. Popieul, “Online adaptation of the Level of Haptic Authority in a lane keeping system considering the driver’s state”, Transportation Research Part F: Traffic Psychology and Behaviour, In press, Sep. 2017. https://doi.org/10.1016/j.trf.2017.08.013
dc.relationE. Rohmer, S. P. N. Singh and M. Freese, “V-REP: A versatile and scalable robot simulation framework”, IEEE/
dc.relationRSJ International Conference on Intelligent Robots and Systems, pp. 1321–1326, Nov. 2013. https://doi.org/10.1109/IROS.2013.6696520
dc.relationF. Conti, F. Barbagli, R. Balaniuk, M. Halg, C. Lu, D. Morris, L. Sentis, J. Warren, O. Khatib and K. Salisbury, “The CHAI libraries”, Proceedings of Eurohaptics 2003, Dublin, Ireland, pp. 496–500, 2003.
dc.relationD. J. Block, M. B. Michelotti and R. S. Sreenivas, “Application of the Novint Falcon haptic device as an actuator in real-time control”, Paladyn, Journal of Behavioral Robotics, vol. 4, no. 3, 182–193, 2013. https://doi.org/10.2478/pjbr-2013-0017
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dc.rightsCC0 1.0 Universal
dc.rightshttp://creativecommons.org/publicdomain/zero/1.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.sourceINGE CUC
dc.sourcehttps://revistascientificas.cuc.edu.co/ingecuc/article/view/2048
dc.subjectTelerobótica
dc.subjectRobots móviles
dc.subjectControl compartido
dc.subjectHáptica
dc.subjectEEG
dc.subjectInterfaz cerebro computador
dc.subjectTelerobotics
dc.subjectBrain computer
dc.subjectInterface
dc.subjectMobile robots
dc.subjectShared control
dc.subjectHaptics
dc.titleEvaluación de las emociones de usuarios en tareas con realimentación háptica utilizado el dispositivo Emotiv Insight
dc.titleAssessment of the users emotions in haptic feedback tasks using the Emotiv Insight device
dc.typeArtículo de revista
dc.typehttp://purl.org/coar/resource_type/c_6501
dc.typeText
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/submittedVersion
dc.typehttp://purl.org/redcol/resource_type/ART
dc.typeinfo:eu-repo/semantics/acceptedVersion
dc.typehttp://purl.org/coar/version/c_ab4af688f83e57aa


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