Please use this identifier to cite or link to this item:
https://ruomoplus.lib.uom.gr/handle/8000/1004
Title: | Mobile Sensing for Emotion Recognition in Smartphones: A Literature Review on Non-Intrusive Methodologies | Authors: | Tzafilkou, Katerina Economides, Anastasios Protogeros, Nicolaos |
Author Department Affiliations: | Department of Economics Department of Economics Department of Accounting & Finance |
Author School Affiliations: | School of Economic and Regional Studies School of Economic and Regional Studies School of Business Administration |
Subjects: | FRASCATI__Social sciences__Psychology__Psychology (including: human-machine relations) FRASCATI__Social sciences__Psychology__Psychology (including: human-machine relations) |
Keywords: | affective computing mobile emotion sensing mobile learning emotion recognition multimodal signals smartphone sensing |
Issue Date: | 2022 | Journal: | International Journal of Human–Computer Interaction | ISSN: | 1044-7318 1532-7590 |
Volume: | 38 | Issue: | 11 | Start page: | 1037 | End page: | 1051 | Abstract: | This 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. |
URI: | https://doi.org/10.1080/10447318.2021.1979290 https://ruomoplus.lib.uom.gr/handle/8000/1004 |
DOI: | 10.1080/10447318.2021.1979290 | Corresponding Item Departments: | Department of Economics Department of Economics Department of Accounting & Finance |
Appears in Collections: | Articles |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Ruomo_MobileEmotionSensing.pdf | 876,6 kB | Adobe PDF | View/Open |
SCOPUSTM
Citations
11
checked on Nov 7, 2024
Page view(s)
18
checked on Nov 13, 2024
Download(s)
48
checked on Nov 13, 2024
Google ScholarTM
Check
Altmetric
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.