TY - JOUR
T1 - Low-cost assessment of user experience through EEG signals
AU - Cano, Sandra
AU - Araujo, Nelson
AU - Guzman, Cristian
AU - RUSU, ALEXANDRU CRISTIAN
AU - Albiol-Pérez, Sergio
N1 - Funding Information:
This work was supported in part by the Gobierno de Aragón, Departamento de Industria e Innovación, and in part by the Fondo Social Europeo Construyendo Europa desde Aragón and by grants from the Instituto de Salud Carlos III, Spanish Government and European Regional Development Fund, A way to build Europe under Grant FIS. PI17/00465.
Publisher Copyright:
© 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - EEG 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.
AB - EEG 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.
KW - EEG signals
KW - Low-cost technologies
KW - Player eXperience
KW - User eXperience
KW - Video games
UR - http://www.scopus.com/inward/record.url?scp=85102744439&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2020.3017685
DO - 10.1109/ACCESS.2020.3017685
M3 - Article
AN - SCOPUS:85102744439
VL - 8
SP - 158475
EP - 158487
JO - IEEE Access
JF - IEEE Access
SN - 2169-3536
ER -