This paper investigates the possibility of using information from Electroencephalography (EEG), obtained through a light and inexpensive Brain Computer Interface (BCI), in order to dynamically adjust the difficulty of an educational video game and adapt the level of challenge to players' abilities. In this experiment, attention levels of Tetris players - measured with the BCI - have been evaluated as a function of game difficulty. Processing of the data re-vealed that both in intra- and inter- player analysis, an increase in game difficul-ty was followed by an increase in attention. These results come in accordance with similar experiments performed with a 19 sensor EEG cap, as opposed to the single-dry-sensor BCI used here. These findings give new possibilities in the development of educational games that adapt to the mental state of play-er/learner.
Patsis, G, Sahli, H, Verhelst, W & De Troyer, O 2013, Evaluation of Attention Levels in a Tetris Game Using a Brain Computer Interface. in C Sandra, W Stephan, M Alessandro & S Giovanni (eds), User Modeling, Adaptation, and Personalization. vol. 7899, LNCS, Springer, pp. 127-138, 21th International Conference, UMAP 2013, Rome, Italy, 14/06/13.
Patsis, G., Sahli, H., Verhelst, W., & De Troyer, O. (2013). Evaluation of Attention Levels in a Tetris Game Using a Brain Computer Interface. In C. Sandra, W. Stephan, M. Alessandro, & S. Giovanni (Eds.), User Modeling, Adaptation, and Personalization (Vol. 7899, pp. 127-138). (LNCS). Springer.
@inproceedings{73f957d25cd642998915716394c70571,
title = "Evaluation of Attention Levels in a Tetris Game Using a Brain Computer Interface",
abstract = "This paper investigates the possibility of using information from Electroencephalography (EEG), obtained through a light and inexpensive Brain Computer Interface (BCI), in order to dynamically adjust the difficulty of an educational video game and adapt the level of challenge to players' abilities. In this experiment, attention levels of Tetris players - measured with the BCI - have been evaluated as a function of game difficulty. Processing of the data re-vealed that both in intra- and inter- player analysis, an increase in game difficul-ty was followed by an increase in attention. These results come in accordance with similar experiments performed with a 19 sensor EEG cap, as opposed to the single-dry-sensor BCI used here. These findings give new possibilities in the development of educational games that adapt to the mental state of play-er/learner.",
keywords = "brain computer interface, e-learning, adaptivity, serious games",
author = "Georgios Patsis and Hichem Sahli and Werner Verhelst and {De Troyer}, Olga",
note = "Carberry Sandra, Weibelzahl Stephan, Micarelli Alessandro, and Semeraro Giovanni; 21th International Conference, UMAP 2013, UMAP 2013 ; Conference date: 14-06-2013 Through 16-06-2013",
year = "2013",
language = "English",
isbn = "978-3-642-38843-9",
volume = "7899",
series = "LNCS",
publisher = "Springer",
pages = "127--138",
editor = "Carberry Sandra and Weibelzahl Stephan and Micarelli Alessandro and Semeraro Giovanni",
booktitle = "User Modeling, Adaptation, and Personalization",
}