DEVELOPMENT OF A MEASUREMENT AND INFORMATION EEG SYSTEM FOR INVESTIGATING THE INFLUENCE OF COGNITIVE STATES ON SPATIAL THINKING AND LOGICAL REASONING
Keywords:
EEG bandwidth, machine learning, cognitive neuroscience, Python
Abstract
This paper focuses on the analysis of EEG (electroencephalographic) signals measured during gameplay of the video game „Minesweeper". The research explores an innovative approach to understanding how cognitive processes influence performance in the "Minesweeper" game. Data collected through EEG were used to train an Artificial Intelligence model, specifically a Machine Learning model. This model's task is to predict player performance based on EEG signals, specifically: the game outcome (win or loss) and the completion time (in seconds).
References
[1] Jihyeon Ha, Wanjoo Park, Sang In Park, Chang-Hwan Im, Laehyun Kim, EEG response to game-craving according to personal preference for games, Social Cognitive and Affective Neuroscience, Volume 16, Issue 9, October 2021, Pages 995–1005, https://doi.org/10.1093/scan/nsaa131
[2] Choi E, Shin SH, Ryu JK, Jung KI, Kim SY, Park MH. Commercial video games and cognitive functions: video game genres and modulating factors of cognitive enhancement. Behav Brain Funct. 2020 Feb 3;16(1):2. doi: 10.1186/s12993-020-0165-z. PMID: 32014027; PMCID: PMC6996164.
[3] Liao, Lun-De & Chen, Chi-Yu & Wang, I-Jan & Chen, Sheng-Fu & Li, Shih-Yu & Chen, Bo-Wei & Chang, Jyh-Yeong & Lin, Chin-Teng. (2012). Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors. Journal of neuro-engineering and rehabilitation. 9. 5. 10.1186/1743-0003-9-5.
[4] Chen, D., James, J., Bao, F.S., Ling, C., Fan, T. (2016). Relationship Between Video Game Events and Player Emotion Based on EEG. In: Kurosu, M. (eds) Human-Computer Interaction. Novel User Experiences. HCI 2016. Lecture Notes in Computer Science(), vol 9733. Springer, Cham. https://doi.org/10.1007/978-3-319-39513-5_35
[5] Ren, Shen & Babiloni, Fabio & Thakor, Nitish & Bezerianos, Anastasios. (2016). Real-Time Workload Assessment Using EEG Signals in Virtual Reality Environment. 10.1007/978-3-319-32703-7_259.
[6] L. Wang, X. Ding, W. Zhang and S. Yang, "Differences in EEG Microstate Induced by Gaming: A Comparison Between the Gaming Disorder Individual, Recreational Game Users and Healthy Controls," in IEEE Access, vol. 9, pp. 32549-32558, 2021, doi: 10.1109/ACCESS.2021.3060112.
[7] Becerra, D.J. (2015). Algorithmic Approaches to Playing Minesweeper.
[2] Choi E, Shin SH, Ryu JK, Jung KI, Kim SY, Park MH. Commercial video games and cognitive functions: video game genres and modulating factors of cognitive enhancement. Behav Brain Funct. 2020 Feb 3;16(1):2. doi: 10.1186/s12993-020-0165-z. PMID: 32014027; PMCID: PMC6996164.
[3] Liao, Lun-De & Chen, Chi-Yu & Wang, I-Jan & Chen, Sheng-Fu & Li, Shih-Yu & Chen, Bo-Wei & Chang, Jyh-Yeong & Lin, Chin-Teng. (2012). Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors. Journal of neuro-engineering and rehabilitation. 9. 5. 10.1186/1743-0003-9-5.
[4] Chen, D., James, J., Bao, F.S., Ling, C., Fan, T. (2016). Relationship Between Video Game Events and Player Emotion Based on EEG. In: Kurosu, M. (eds) Human-Computer Interaction. Novel User Experiences. HCI 2016. Lecture Notes in Computer Science(), vol 9733. Springer, Cham. https://doi.org/10.1007/978-3-319-39513-5_35
[5] Ren, Shen & Babiloni, Fabio & Thakor, Nitish & Bezerianos, Anastasios. (2016). Real-Time Workload Assessment Using EEG Signals in Virtual Reality Environment. 10.1007/978-3-319-32703-7_259.
[6] L. Wang, X. Ding, W. Zhang and S. Yang, "Differences in EEG Microstate Induced by Gaming: A Comparison Between the Gaming Disorder Individual, Recreational Game Users and Healthy Controls," in IEEE Access, vol. 9, pp. 32549-32558, 2021, doi: 10.1109/ACCESS.2021.3060112.
[7] Becerra, D.J. (2015). Algorithmic Approaches to Playing Minesweeper.
Published
2024-05-07
Section
Biomedical Engineering
