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A bci based alerting system for attention recovery of UAV operators

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dc.contributor.authorPark, Jonghyuk-
dc.contributor.authorPark, Jonghun-
dc.contributor.authorShin, Dongmin-
dc.contributor.authorChoi, Yerim-
dc.date.accessioned2021-06-22T04:27:32Z-
dc.date.available2021-06-22T04:27:32Z-
dc.date.issued2021-04-
dc.identifier.issn1424-8220-
dc.identifier.issn1424-3210-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/591-
dc.description.abstractAs unmanned aerial vehicles have become popular, the number of accidents caused by an operator’s inattention have increased. To prevent such accidents, the operator should maintain an attention status. However, limited research has been conducted on the brain-computer interface (BCI)-based system with an alerting module for the operator’s attention recovery of unmanned aerial vehicles. Therefore, we introduce a detection and alerting system that prevents an unmanned aerial vehicle operator from falling into inattention status by using the operator’s electroencephalogram signal. The proposed system consists of the following three components: a signal processing module, which collects and preprocesses an electroencephalogram signal of an operator, an inattention detection module, which determines whether an inattention status occurred based on the preprocessed signal, and, lastly, an alert providing module that presents stimulus to an operator when inattention is detected. As a result of evaluating the performance with a real-world dataset, it was shown that the proposed system successfully contributed to the recovery of operator attention in the evaluating dataset, although statistical significance could not be established due to the small number of subjects. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.-
dc.format.extent20-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI AG-
dc.titleA bci based alerting system for attention recovery of UAV operators-
dc.typeArticle-
dc.publisher.location스위스-
dc.identifier.doi10.3390/s21072447-
dc.identifier.scopusid2-s2.0-85103480602-
dc.identifier.wosid000638875400001-
dc.identifier.bibliographicCitationSensors, v.21, no.7, pp 1 - 20-
dc.citation.titleSensors-
dc.citation.volume21-
dc.citation.number7-
dc.citation.startPage1-
dc.citation.endPage20-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaInstruments & Instrumentation-
dc.relation.journalWebOfScienceCategoryChemistry, Analytical-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryInstruments & Instrumentation-
dc.subject.keywordPlusAccidents-
dc.subject.keywordPlusAircraft detection-
dc.subject.keywordPlusAntennas-
dc.subject.keywordPlusBrain computer interface-
dc.subject.keywordPlusElectroencephalography-
dc.subject.keywordPlusRecovery-
dc.subject.keywordPlusSignal processing-
dc.subject.keywordPlusUnmanned aerial vehicles (UAV)-
dc.subject.keywordPlusAlerting systems-
dc.subject.keywordPlusDetection modules-
dc.subject.keywordPlusElectroencephalogram signals-
dc.subject.keywordPlusReal-world-
dc.subject.keywordPlusStatistical significance-
dc.subject.keywordPlusThree component-
dc.subject.keywordPlusComputer system recovery-
dc.subject.keywordAuthorAlerting system-
dc.subject.keywordAuthorAttention recovery-
dc.subject.keywordAuthorBrain computer interaction-
dc.subject.keywordAuthorEEG-signal-
dc.subject.keywordAuthorGraphical user interface-
dc.subject.keywordAuthorUnmanned aerial vehicle-
dc.identifier.urlhttps://www.mdpi.com/1424-8220/21/7/2447-
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Shin, Dong min
ERICA 공학대학 (DEPARTMENT OF INDUSTRIAL & MANAGEMENT ENGINEERING)
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