Brain Computer Interface: Deep Learning Approach to Predict Human Emotion Recognition

IEEE International Conference on Systems, Man, and Cybernetics (SMC 2022) - -2022

Authors

Ardito Carmelo, Bortone Ilaria, Colafiglio Tommaso, Di Noia Tommaso, Di Sciascio Eugenio, Lofù Domenico, Narducci Fedelucio, Sardone Rodolfo, Sorino Paolo

Abstract

Distance education has experienced profound changes due to the introduction of new technologies, especially mobile devices of different types. It is necessary to define new learning techniques which are able to capture students’ attention and to engage them in their learning activities, reducing problems like distraction generated by the use of the device itself and/or by the surrounding environment. Game-based learning is a valuable possibility. The excursion-game has been recently proposed to support pupils learning history during visits to historical sites; its goal is to make the visit and the overall experience of cultural heritage more engaging. This paper describes the approach followed in the design of the system implementing the excursion-game; it takes into account an end-user development perspective in order to allow domain experts, i.e., experts in history and cultural heritage, contributing to design excursion-games for a wide set of historical sites.

Download: SMC_2022_BCI_[Camera_Ready].pdf

DOI

https://doi.org/https://www.doi.org/10.1109/SMC53654.2022.9945554

BibTex references

@Article{ABCDDLNSS22,
  author       = "Ardito, Carmelo and Bortone, Ilaria and Colafiglio, Tommaso and Di Noia, Tommaso and Di Sciascio, Eugenio and Lof\`u, Domenico and Narducci, Fedelucio and Sardone, Rodolfo and Sorino, Paolo",
  title        = "Brain Computer Interface: Deep Learning Approach to Predict Human Emotion Recognition",
  journal      = "IEEE International Conference on Systems, Man, and Cybernetics (SMC 2022)",
  year         = "2022",
  url          = "http://sisinflab.poliba.it/Publications/2022/ABCDDLNSS22"

}