000095823 001__ 95823 000095823 005__ 20210902121802.0 000095823 0247_ $$2doi$$a10.1109/ACCESS.2020.3017685 000095823 0248_ $$2sideral$$a120162 000095823 037__ $$aART-2020-120162 000095823 041__ $$aeng 000095823 100__ $$aCano, S. 000095823 245__ $$aLow-Cost Assessment of User eXperience Through EEG Signals 000095823 260__ $$c2020 000095823 5060_ $$aAccess copy available to the general public$$fUnrestricted 000095823 5203_ $$aEEG signals are an important tool for monitoring the brain activity of a person, but equipment, expertise and infrastructure are required. EEG technologies are generally expensive, thus few people are normally able to use them. However, some low-cost technologies are now available. One of these is OPENBCI, but it seems that it is yet to be widely employed in Human-Computer Interaction. In this study, we used OPENBCI technology to capture EEG signals linked to brain activity in ten subjects as they interacted with two video games: Candy Crush and Geometry Dash. The experiment aimed to capture the signals while the players interacted with the video games in several situations. The results show differences due to the absence/presence of sound; players appear to be more relaxed without sound. In addition, consistent analysis of the EEG data, meCue 2.0 and SAM data showed high consistency. The evidence demonstrates that interesting results are able to be gathered based on low-cost EEG (standard) signal-based technologies. 000095823 536__ $$9info:eu-repo/grantAgreement/ES/DGA-FEDER/Construyendo Europa desde Aragón$$9info:eu-repo/grantAgreement/EUR/ERDF/A way to build Europe$$9info:eu-repo/grantAgreement/ES/ISCIII-FIS/PI17-00465 000095823 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/ 000095823 590__ $$a3.367$$b2020 000095823 591__ $$aCOMPUTER SCIENCE, INFORMATION SYSTEMS$$b65 / 162 = 0.401$$c2020$$dQ2$$eT2 000095823 591__ $$aTELECOMMUNICATIONS$$b36 / 91 = 0.396$$c2020$$dQ2$$eT2 000095823 591__ $$aENGINEERING, ELECTRICAL & ELECTRONIC$$b94 / 273 = 0.344$$c2020$$dQ2$$eT2 000095823 592__ $$a0.586$$b2020 000095823 593__ $$aComputer Science (miscellaneous)$$c2020$$dQ1 000095823 593__ $$aMaterials Science (miscellaneous)$$c2020$$dQ1 000095823 593__ $$aEngineering (miscellaneous)$$c2020$$dQ1 000095823 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000095823 700__ $$aAraujo, N. 000095823 700__ $$aGuzman, C. 000095823 700__ $$aRusu, C. 000095823 700__ $$0(orcid)0000-0002-6280-1474$$aAlbiol-Perez, S.$$uUniversidad de Zaragoza 000095823 7102_ $$15007$$2035$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Arquit.Tecnología Comput. 000095823 773__ $$g8 (2020), 158475-158487$$pIEEE Access$$tIEEE Access$$x2169-3536 000095823 8564_ $$s1237543$$uhttps://zaguan.unizar.es/record/95823/files/texto_completo.pdf$$yVersión publicada 000095823 8564_ $$s556504$$uhttps://zaguan.unizar.es/record/95823/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000095823 909CO $$ooai:zaguan.unizar.es:95823$$particulos$$pdriver 000095823 951__ $$a2021-09-02-09:56:03 000095823 980__ $$aARTICLE