Towards EEG-based BCI driven by emotions for addressing BCI-Illiteracy: a meta-analytic review

• Type: Article in International Scientific Journal
• Date: 2018-08

Authors

M. Spezialetti (Author) Other; L. Cinque (Author) Other; João Manuel R. S. Tavares (Author) FEUP; G. Placidi (Author) Other

Journal

The Journal is awaiting validation by the Administrative Services.

Title: BEHAVIOUR & INFORMATION TECHNOLOGY

Vol. 37

Pages: 855-871

ISSN: 0144-929X

Indexing

ISI Web of Knowledge - 0 Citations

ISI Web of Science

Scopus - 21 Citations

INSPEC

Scientific classification

CORDIS: Technological sciences

FOS: Medical and Health sciences

Other information

Authenticus ID: P-00P-0TK

DOI: 10.1080/0144929x.2018.1485745

Abstract (EN): Many critical aspects affect the correct operation of a Brain Computer Interface. The term BCI-illiteracy' describes the impossibility of using a BCI paradigm. At present, a universal solution does not exist and seeking innovative protocols to drive a BCI is mandatory. This work presents a meta-analytic review on recent advances in emotions recognition with the perspective of using emotions as voluntary, stimulus-independent, commands for BCIs. 60 papers, based on electroencephalography measurements, were selected to evaluate what emotions have been most recognised and what brain regions were activated by them. It was found that happiness, sadness, anger and calm were the most recognised emotions. Relevant discriminant locations for emotions recognition and for the particular case of discrete emotions recognition were identified in the temporal, frontal and parietal areas. The meta-analysis was mainly performed on stimulus-elicited emotions, due to the limited amount of literature about self-induced emotions. The obtained results represent a good starting point for the development of BCI driven by emotions and allow to: (1) ascertain that emotions are measurable and recognisable one from another (2) select a subset of most recognisable emotions and the corresponding active brain regions.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 17