2023
DOI: 10.1109/jproc.2023.3286445
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Approaches, Applications, and Challenges in Physiological Emotion Recognition—A Tutorial Overview

Abstract: An automatic emotion recognition system can serve as a fundamental framework for various applications in daily life from monitoring emotional well-being to improving the quality of life through better emotion regulation. Understanding the process of emotion manifestation becomes crucial for building emotion recognition systems. An emotional experience results in changes not only in interpersonal behavior but also in physiological responses. Physiological signals are one of the most reliable means for recognizi… Show more

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Cited by 13 publications
(4 citation statements)
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“…The demand for labeled data for robust models increases the reliance on self-reports, which can be time consuming for participants. Researchers are exploring semi-supervised methods to reduce the need for labeled data and improve emotion recognition research [34].…”
Section: Self-assessment Of Emotionsmentioning
confidence: 99%
“…The demand for labeled data for robust models increases the reliance on self-reports, which can be time consuming for participants. Researchers are exploring semi-supervised methods to reduce the need for labeled data and improve emotion recognition research [34].…”
Section: Self-assessment Of Emotionsmentioning
confidence: 99%
“…A comprehensive discussion on the Machine Learning theory applied to the emotion recognition field goes beyond the scope of this article. Interested readers can refer to introductory tutorials, such as Zhang et al ( 2020 ) and Can et al ( 2023 ).…”
Section: Introductionmentioning
confidence: 99%
“…Despite notable strides in this domain, the synthesis of accurate and contextually rich captions remains a formidable challenge [4]. Contemporary methodologies, particularly those rooted in deep learning frameworks, encounter persistent hurdles in capturing the nuanced relationships, intricate details, and contextual subtleties present within images [5,6].…”
Section: Introductionmentioning
confidence: 99%