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dc.contributor.authorDzedzickis, Andrius
dc.contributor.authorKaklauskas, Artūras
dc.contributor.authorBučinskas, Vytautas
dc.date.accessioned2023-09-18T20:16:54Z
dc.date.available2023-09-18T20:16:54Z
dc.date.issued2020
dc.identifier.issn1424-8220
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/148524
dc.description.abstractAutomated emotion recognition (AEE) is an important issue in various fields of activities which use human emotional reactions as a signal for marketing, technical equipment, or human– robot interaction. This paper analyzes scientific research and technical papers for sensor use analysis, among various methods implemented or researched. This paper covers a few classes of sensors, using contactless methods as well as contact and skin-penetrating electrodes for human emotion detection and the measurement of their intensity. The results of the analysis performed in this paper present applicable methods for each type of emotion and their intensity and propose their classification. The classification of emotion sensors is presented to reveal area of application and expected outcomes from each method, as well as their limitations. This paper should be relevant for researchers using human emotion evaluation and analysis, when there is a need to choose a proper method for their purposes or to find alternative decisions. Based on the analyzed human emotion recognition sensors and methods, we developed some practical applications for humanizing the Internet of Things (IoT) and affective computing systems.eng
dc.formatPDF
dc.format.extentp. 1-41
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyMEDLINE
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyScopus
dc.source.urihttps://doi.org/10.3390/s20030592
dc.titleHuman emotion recognition: review of sensors and methods
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.accessRightsThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
dcterms.references199
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyMechanikos fakultetas / Faculty of Mechanics
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.subject.researchfieldT 009 - Mechanikos inžinerija / Mechanical enginering
dc.subject.vgtuprioritizedfieldsMC03 - Išmaniosios įterptinės sistemos / Smart embedded systems
dc.subject.ltspecializationsL104 - Nauji gamybos procesai, medžiagos ir technologijos / New production processes, materials and technologies
dc.subject.enhuman emotions
dc.subject.enemotion perception
dc.subject.enphysiologic sensors
dcterms.sourcetitleSensors
dc.description.issueiss. 3
dc.description.volumevol. 20
dc.publisher.nameMDPI
dc.publisher.cityBasel
dc.identifier.doi000517786200016
dc.identifier.doi10.3390/s20030592
dc.identifier.elaba49285617


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