A Modular Framework for EEG Web Based Binary Brain Computer Interfaces to Recover Communication Abilities in Impaired People.
A Brain Computer Interface (BCI) allows communication for impaired people unable to express their intention with common channels. Electroencephalography (EEG) represents an effective tool to allow the implementation of a BCI. The present paper describes a modular framework for the implementation of...
| Publicado en: | Journal of Medical Systems Vol. 40; no. 1; pp. 1 - 15 |
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| Autores principales: | , , , |
| Formato: | algorithm equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jan2016
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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=115925227&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 115925227 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Jan2016 vid: 40 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 115925227 115925227 115925227 10.1007/s10916-015-0402-4 115925227 ppf: 1 ppct: 14 formats: fmt: @attributes: type: P tig: atl: A Modular Framework for EEG Web Based Binary Brain Computer Interfaces to Recover Communication Abilities in Impaired People. aug: au: Placidi, Giuseppe Petracca, Andrea Spezialetti, Matteo Iacoviello, Daniela affil: Department of Life, Health and Environmental Sciences, University of L'Aquila, Via Vetoio 67100 L'Aquila Italy sug: subj: Electroencephalography Electrical Equipment and Supplies Brain Computers and Computerization Communication Skills Persons with Disabilities Assistive Technology User-Computer Interface Systems Design Computers, Portable World Wide Web Signal Processing, Computer Assisted HTML Calibration Writing Communication Human Male Female Young Adult Adult Italy Algorithms Funding Source Adult: 19-44 years Male Female ab: A Brain Computer Interface (BCI) allows communication for impaired people unable to express their intention with common channels. Electroencephalography (EEG) represents an effective tool to allow the implementation of a BCI. The present paper describes a modular framework for the implementation of the graphic interface for binary BCIs based on the selection of symbols in a table. The proposed system is also designed to reduce the time required for writing text. This is made by including a motivational tool, necessary to improve the quality of the collected signals, and by containing a predictive module based on the frequency of occurrence of letters in a language, and of words in a dictionary. The proposed framework is described in a top-down approach through its modules: signal acquisition, analysis, classification, communication, visualization, and predictive engine. The framework, being modular, can be easily modified to personalize the graphic interface to the needs of the subject who has to use the BCI and it can be integrated with different classification strategies, communication paradigms, and dictionaries/languages. The implementation of a scenario and some experimental results on healthy subjects are also reported and discussed: the modules of the proposed scenario can be used as a starting point for further developments, and application on severely disabled people under the guide of specialized personnel. pubtype: Academic Journal doctype: algorithm equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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