Extracting neurophysiological signals reflecting users' emotional and affective responses to BCI use: A systematic literature review.

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.

journal_name

NeuroRehabilitation

journal_title

NeuroRehabilitation

authors

Liberati G,Federici S,Pasqualotto E

doi

10.3233/NRE-151266

subject

Has Abstract

pub_date

2015-01-01 00:00:00

pages

341-58

issue

3

eissn

1053-8135

issn

1878-6448

pii

NRE151266

journal_volume

37

pub_type

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