Brain Computer Interfaces (BCIs) use measurements of the voluntary brain activity for driving a communication system, by means of the activation of mental tasks. In recent literature, a novel activation paradigm, based on the self-induction of emotions, has been proposed and some classification strategies for self-induced emotions have been designed, together with a modular framework for the implementation of binary BCIs. We extended the BCI system, to manage the multi-class scenario, in order to increase the number of recognizable commands, thus improving the efficacy of the communication. The objective was to provide a correction function that would allow the increase of the accuracy, without the overhead of a verification method. A poll oriented classification algorithm was used in conjunction with a matrix based graphic interface to allow the user to communicate through three self-induced emotional states: the disgust produced by remembering a bad odor, the good sensation produced by remembering the odor of a good fragrance and a relaxing state. The proposed system was tested on a healthy subject. Preliminary results were reported and discussed.

BCI driven by self-induced emotions: a multi-class study / Placidi, Giuseppe; Polsinelli, Matteo; Spezialetti, Matteo; Cinque, Luigi. - (2018), pp. 1-6. ((Intervento presentato al convegno 13th IEEE International Symposium on Medical Measurements and Applications, MeMeA 2018 tenutosi a Rome; Italy [10.1109/MeMeA.2018.8438817].

BCI driven by self-induced emotions: a multi-class study

Spezialetti, Matteo;Cinque, Luigi
2018

Abstract

Brain Computer Interfaces (BCIs) use measurements of the voluntary brain activity for driving a communication system, by means of the activation of mental tasks. In recent literature, a novel activation paradigm, based on the self-induction of emotions, has been proposed and some classification strategies for self-induced emotions have been designed, together with a modular framework for the implementation of binary BCIs. We extended the BCI system, to manage the multi-class scenario, in order to increase the number of recognizable commands, thus improving the efficacy of the communication. The objective was to provide a correction function that would allow the increase of the accuracy, without the overhead of a verification method. A poll oriented classification algorithm was used in conjunction with a matrix based graphic interface to allow the user to communicate through three self-induced emotional states: the disgust produced by remembering a bad odor, the good sensation produced by remembering the odor of a good fragrance and a relaxing state. The proposed system was tested on a healthy subject. Preliminary results were reported and discussed.
9781538633915
File allegati a questo prodotto
File Dimensione Formato  
Placidi_BCI_2018.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 158.58 kB
Formato Adobe PDF
158.58 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11573/1232121
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact