Authors:
Dize Hilviu
1
;
Stefano Vincenzi
2
;
Giovanni Chiarion
3
;
Claudio Mattutino
2
;
Silvestro Roatta
4
;
Andrea Calvo
5
;
6
;
7
;
Francesca M. Bosco
1
;
6
and
Cristina Gena
2
Affiliations:
1
Department of Psychology, University of Turin, Via Verdi 10, 10124, Turin, Italy
;
2
Department of Computer Science, University of Turin, Corso Svizzera 185, 10149, Turin, Italy
;
3
Department of Electronics and Telecommunications, Polytechnic of Turin, Corso Duca degli Abruzzi 24, 10129, Turin, Italy
;
4
Rita Levi Montalcini Department of Neuroscience, University of Turin, Corso Raffaello 30, 10125, Turin, Italy
;
5
Neurology, Hospital Department of Neuroscience and Mental Health, Città della Salute e della Scienza Hospital of Turin, Corso Bramante 88, 10126, Turin, Italy
;
6
Neuroscience Institute of Turin, University of Turin, Regione Gonzole 10, 10043, Orbassano, Italy
;
7
Rita Levi Montalcini Department of Neuroscience, University of Turin, Via Cherasco 15, 10126, Turin, Italy
Keyword(s):
Human-Computer Interaction, Brain-Computer Interaction, Brain-Computer Interface, Electroencephalography, EEG-based BCI, Cognitive Task, Endogenous Task.
Abstract:
Brain-Computer Interfaces allow interaction between the voluntarily produced human cerebral activity and a computer. The output produced by the user’s performance can serve as an input to the technologic device that can decode this information and transform it to a command. Literature has usually focused on processing and classification often neglecting the importance of the mental tasks used to elicit and modulate the cerebral activity. In this paper, we review previous mental tasks used in literature: motor imagery, spatial navigation, geometric figure rotation, imagery of familiar faces, auditory imagery and math imagery. Then, we propose a set of these tasks modified to maximize the user’s performance during the execution of mental tasks.