{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:38:42Z","timestamp":1760146722958,"version":"build-2065373602"},"reference-count":180,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T00:00:00Z","timestamp":1733443200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"2022\/23 Aston Pump Priming Scheme of Aston University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Human engagement is a vital test research area actively explored in cognitive science and user experience studies. The rise of big data and digital technologies brings new opportunities into this field, especially in autonomous systems and smart applications. This article reviews the latest sensors, current advances of estimation methods, and existing domains of application to guide researchers and practitioners to deploy engagement estimators in various use cases from driver drowsiness detection to human\u2013robot interaction (HRI). Over one hundred references were selected, examined, and contrasted in this review. Specifically, this review focuses on accuracy and practicality of use in different scenarios regarding each sensor modality, as well as current opportunities that greater automatic human engagement estimation could unlock. It is highlighted that multimodal sensor fusion and data-driven methods have shown significant promise in enhancing the accuracy and reliability of engagement estimation. Upon compiling the existing literature, this article addresses future research directions, including the need for developing more efficient algorithms for real-time processing, generalization of data-driven approaches, creating adaptive and responsive systems that better cater to individual needs, and promoting user acceptance.<\/jats:p>","DOI":"10.3390\/a17120560","type":"journal-article","created":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T09:55:20Z","timestamp":1733478920000},"page":"560","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Sensors, Techniques, and Future Trends of Human-Engagement-Enabled Applications: A Review"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6098-115X","authenticated-orcid":false,"given":"Zhuangzhuang","family":"Dai","sequence":"first","affiliation":[{"name":"Department of Applied AI & Robotics, Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9360-0985","authenticated-orcid":false,"given":"Vincent Gbouna","family":"Zakka","sequence":"additional","affiliation":[{"name":"Department of Applied AI & Robotics, Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2616-1120","authenticated-orcid":false,"given":"Luis J.","family":"Manso","sequence":"additional","affiliation":[{"name":"Department of Applied AI & Robotics, Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9109-5188","authenticated-orcid":false,"given":"Martin","family":"Rudorfer","sequence":"additional","affiliation":[{"name":"Department of Applied AI & Robotics, Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4659-3035","authenticated-orcid":false,"given":"Ulysses","family":"Bernardet","sequence":"additional","affiliation":[{"name":"Department of Applied AI & Robotics, Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0419-3869","authenticated-orcid":false,"given":"Johanna","family":"Zumer","sequence":"additional","affiliation":[{"name":"School of Psychology, Institute of Health and Neurodevelopment, Aston University, Birmingham B4 7ET, UK"}]},{"given":"Manolya","family":"Kavakli-Thorne","sequence":"additional","affiliation":[{"name":"Aston Digital Futures Institute, Aston University, Birmingham B4 7ET, UK"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3234149","article-title":"Engagement in HCI: Conception, Theory and Measurement","volume":"51","author":"Doherty","year":"2018","journal-title":"ACM Comput. 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