Affiliations: [a] Université Catholique de Louvain, Institute of Neuroscience, Louvain, Belgium | [b] Università di Perugia, Department of Philosophy, Social & Human Sciences and Education, Perugia, Italy
Correspondence:
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Address for correspondence: Giulia Liberati, Université Catholique de Louvain, Institute of Neuroscience, Louvain, Belgium. Tel.: +32 027645467; Fax: +32 027645465; E-mail: giulia.liberati@uclouvain.be
Abstract: BACKGROUND:Brain–computer interfaces (BCIs) allow persons with impaired mobility to communicate and interact with the environment, supporting goal-directed thinking and cognitive function. Ideally, a BCI should be able to recognize a user’s internal state and adapt to it in real-time, to improve interaction. OBJECTIVE:Our aim was to examine studies investigating the recognition of affective states from neurophysiological signals, evaluating how current achievements can be applied to improve BCIs. METHODS:Following the PRISMA guidelines, we performed a literature search using PubMed and ProQuest databases. We considered peer-reviewed research articles in English, focusing on the recognition of emotions from neurophysiological signals in view of enhancing BCI use. RESULTS:Of the 526 identified records, 30 articles comprising 32 studies were eligible for review. Their analysis shows that the affective BCI field is developing, with a variety of combinations of neuroimaging techniques, selected neurophysiological features, and classification algorithms currently being tested. Nevertheless, there is a gap between laboratory experiments and their translation to everyday situations. CONCLUSIONS:BCI developers should focus on testing emotion classification with patients in ecological settings and in real-time, with more precise definitions of what they are investigating, and communicating results in a standardized way.
