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Title: Mobile Sensing for Emotion Recognition in Smartphones: A Literature Review on Non-Intrusive Methodologies
Authors: Tzafilkou, Katerina
Economides, Anastasios A.
Protogeros, Nicolaos
Type: Article
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
Source: International Journal of Human–Computer Interaction
Volume: 38
Issue: 11
First Page: 1037
Last 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.
ISSN: 1044-7318
Other Identifiers: 10.1080/10447318.2021.1979290
Appears in Collections:Department of Economics

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