Self-induced emotions as alternative paradigm for driving brain–computer interfaces. Issue 5 (2nd November 2019)

• Record Type: Journal Article
• Authors: Placidi, Giuseppe; Polsinelli, Matteo; Spezialetti, Matteo; Cinque, Luigi; Di Giamberardino, Paolo; Iacoviello, Daniela
• Is Part Of: Computer methods in biomechanics and biomedical engineering. Volume 7:Issue 5/6(2019)
• Page Start: 512
• Page End: 519
• Publication Date: 2019-11-02
• Subjects: Brain–computer interface -- signals classification -- self-induced emotions; Imaging systems in biology -- Periodicals; Imaging systems in medicine -- Periodicals; Biomechanics -- Data processing -- Periodicals; Biomedical engineering -- Periodicals; 616.0757
• DOI: 10.1080/21681163.2018.1479312
• Languages: English
• ISSNs: 2168-1163

Abstract

Abstract: A Brain–Computer Interface (BCI) uses measurements of the voluntary brain activity for driving a communication system; it requires the activation of mental tasks. In the last few years, a new paradigm of activation has been used, consisting in the autonomous brain activation through self-induced emotions, remembered on autobiographical basis. In the present paper, such paradigm is implemented and the resulting BCI system is described, from the classification strategy to the graphic user interface necessary for synchronising mental tasks and collecting EEG signals derived by emotions. Moreover, the proposed BCI is used for collecting and classifying signals, from 10 healthy subjects, of two different emotional states: the disgust produced by remembering a bad odour and the good sensation produced by remembering the odour of a good fragrance, with respect to relax. The classifications are performed in a binary mode, by recognising disgust from relax and good sensation from relax, yielding an accuracy greater than 85%.