Please use this identifier to cite or link to this item: https://ruomoplus.lib.uom.gr/handle/8000/1004
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dc.contributor.authorTzafilkou, Katerinael
dc.contributor.authorEconomides, Anastasios A.el
dc.contributor.authorProtogeros, Nicolaosel
dc.date.accessioned2022-09-28T11:05:32Z-
dc.date.accessioned2024-05-16T08:46:11Z-
dc.date.available2022-09-28T11:05:32Z-
dc.date.available2024-05-16T08:46:11Z-
dc.date.issued2022-
dc.identifier.urihttps://doi.org/10.1080/10447318.2021.1979290-
dc.identifier.urihttps://ruomoplus.lib.uom.gr/handle/8000/1004-
dc.description.abstractThis paper aims to provide the reader with a comprehensive background for understanding current knowledge on the use of non-intrusive Mobile Sensing methodologies for emotion recognition in Smartphone devices. We examined the literature on experimental case studies conducted in the domain during the past six years (2015–2020). Search terms identified 95 candidate articles, but inclusion criteria limited the key studies to 30. We analyzed the research objectives (in terms of targeted emotions), the methodology (in terms of input modalities and prediction models) and the findings (in terms of model performance) of these published papers and categorized them accordingly. We used qualitative methods to evaluate and interpret the findings of the collected studies. The results reveal the main research trends and gaps in the field. The study also discusses the research challenges and considers some practical implications for the design of emotion-aware systems within the context of Distance Education.el
dc.language.isoenel
dc.publisherTaylor & Francis-
dc.relation.ispartofInternational Journal of Human–Computer Interactionel
dc.subjectFRASCATI__Social sciences__Psychology__Psychology (including: human-machine relations)el
dc.subjectFRASCATI__Social sciences__Psychology__Psychology (including: human-machine relations)el
dc.subject.otheraffective computingel
dc.subject.othermobile emotion sensingel
dc.subject.othermobile learning emotion recognitionel
dc.subject.othermultimodal signalsel
dc.subject.othersmartphone sensingel
dc.titleMobile Sensing for Emotion Recognition in Smartphones: A Literature Review on Non-Intrusive Methodologiesel
dc.typejournal articleel
dc.identifier.doi10.1080/10447318.2021.1979290-
dc.contributor.affiliationUniversity of Macedonia-
dc.relation.issn1044-7318el
dc.relation.issn1532-7590el
dc.description.volume38el
dc.description.issue11el
dc.description.startpage1037el
dc.description.endpage1051el
local.identifier.ruomoUUID5f34be24-fcb3-46ac-b9aa-8168e13a8ff0-
dc.contributor.departmentDepartment of Economicsel
dc.contributor.departmentDepartment of Economicsel
dc.contributor.departmentDepartment of Accounting & Financeel
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.grantfulltextopen-
item.openairetypejournal article-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
crisitem.journal.journalissn1044-7318-
crisitem.author.deptUniversity of Macedonia-
crisitem.author.deptUniversity of Macedonia-
crisitem.author.deptUniversity of Macedonia-
crisitem.author.departmentDepartment of Economics-
crisitem.author.departmentDepartment of Economics-
crisitem.author.departmentDepartment of Accounting & Finance-
crisitem.author.orcid0000-0003-4092-6492-
crisitem.author.orcid0000-0001-8056-1024-
crisitem.author.orcid0000-0003-2774-5750-
crisitem.author.facultySchool of Economic and Regional Studies-
crisitem.author.facultySchool of Economic and Regional Studies-
crisitem.author.facultySchool of Business Administration-
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