{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,21]],"date-time":"2026-06-21T06:25:34Z","timestamp":1782023134240,"version":"3.54.5"},"reference-count":108,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2020,4,22]],"date-time":"2020-04-22T00:00:00Z","timestamp":1587513600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Energy, Science, Technology, Environment and Climate Change","award":["ICF0001-2018"],"award-info":[{"award-number":["ICF0001-2018"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The ability to detect users\u2019 emotions for the purpose of emotion engineering is currently one of the main endeavors of machine learning in affective computing. Among the more common approaches to emotion detection are methods that rely on electroencephalography (EEG), facial image processing and speech inflections. Although eye-tracking is fast in becoming one of the most commonly used sensor modalities in affective computing, it is still a relatively new approach for emotion detection, especially when it is used exclusively. In this survey paper, we present a review on emotion recognition using eye-tracking technology, including a brief introductory background on emotion modeling, eye-tracking devices and approaches, emotion stimulation methods, the emotional-relevant features extractable from eye-tracking data, and most importantly, a categorical summary and taxonomy of the current literature which relates to emotion recognition using eye-tracking. This review concludes with a discussion on the current open research problems and prospective future research directions that will be beneficial for expanding the body of knowledge in emotion detection using eye-tracking as the primary sensor modality.<\/jats:p>","DOI":"10.3390\/s20082384","type":"journal-article","created":{"date-parts":[[2020,4,23]],"date-time":"2020-04-23T02:10:52Z","timestamp":1587607852000},"page":"2384","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":249,"title":["Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges"],"prefix":"10.3390","volume":"20","author":[{"given":"Jia Zheng","family":"Lim","sequence":"first","affiliation":[{"name":"Evolutionary Computing Laboratory, Faculty of Computing and Informatics, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James","family":"Mountstephens","sequence":"additional","affiliation":[{"name":"Faculty of Computing and Informatics, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2415-5915","authenticated-orcid":false,"given":"Jason","family":"Teo","sequence":"additional","affiliation":[{"name":"Faculty of Computing and Informatics, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"99","DOI":"10.5334\/pb-46-1-2-99","article-title":"Psychopathy and Physiological Detection of Concealed Information: A review","volume":"46","author":"Verschuere","year":"2006","journal-title":"Psychol. 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