Extracting neurophysiological signals reflecting users' emotional and affective responses to BCI use: A systematic literature review.
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 in...
| Publicado en: | NeuroRehabilitation Vol. 37; no. 3; pp. 341 - 359 |
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| Autores principales: | , , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=120051760&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 120051760 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10538135 3RE jtl: NeuroRehabilitation issn: 10538135 maglogo: N pubinfo: dt: 2015 vid: 37 iid: 3 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 120051760 120051760 120051760 10.3233/NRE-151266 120051760 ppf: 341 ppct: 18 formats: fmt: @attributes: type: P tig: atl: Extracting neurophysiological signals reflecting users' emotional and affective responses to BCI use: A systematic literature review. aug: au: Liberati, Giulia Federici, Stefano Pasqualotto, Emanuele affil: Université Catholique de Louvain, Institute of Neuroscience, Louvain, Belgium sug: subj: Assistive Technology Brain-Computer Interfaces Standards Neurophysiology Emotions Affect Human Systematic Review PubMed Algorithms ab: 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. Keywords: Affective brain computer interfaces (aBCI), brain state classification, assistive technology. pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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