dc.contributor.author | Dzedzickis, Andrius | |
dc.contributor.author | Kaklauskas, Artūras | |
dc.contributor.author | Bučinskas, Vytautas | |
dc.date.accessioned | 2023-09-18T20:16:54Z | |
dc.date.available | 2023-09-18T20:16:54Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 1424-8220 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/148524 | |
dc.description.abstract | Automated 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.format | PDF | |
dc.format.extent | p. 1-41 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | MEDLINE | |
dc.relation.isreferencedby | Science Citation Index Expanded (Web of Science) | |
dc.relation.isreferencedby | Scopus | |
dc.source.uri | https://doi.org/10.3390/s20030592 | |
dc.title | Human emotion recognition: review of sensors and methods | |
dc.type | Straipsnis Web of Science DB / Article in Web of Science DB | |
dcterms.accessRights | This 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.references | 199 | |
dc.type.pubtype | S1 - Straipsnis Web of Science DB / Web of Science DB article | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.faculty | Mechanikos fakultetas / Faculty of Mechanics | |
dc.contributor.faculty | Statybos fakultetas / Faculty of Civil Engineering | |
dc.subject.researchfield | T 009 - Mechanikos inžinerija / Mechanical enginering | |
dc.subject.vgtuprioritizedfields | MC03 - Išmaniosios įterptinės sistemos / Smart embedded systems | |
dc.subject.ltspecializations | L104 - Nauji gamybos procesai, medžiagos ir technologijos / New production processes, materials and technologies | |
dc.subject.en | human emotions | |
dc.subject.en | emotion perception | |
dc.subject.en | physiologic sensors | |
dcterms.sourcetitle | Sensors | |
dc.description.issue | iss. 3 | |
dc.description.volume | vol. 20 | |
dc.publisher.name | MDPI | |
dc.publisher.city | Basel | |
dc.identifier.doi | 000517786200016 | |
dc.identifier.doi | 10.3390/s20030592 | |
dc.identifier.elaba | 49285617 | |