{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T16:02:24Z","timestamp":1772121744656,"version":"3.50.1"},"reference-count":85,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2015,5,12]],"date-time":"2015-05-12T00:00:00Z","timestamp":1431388800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This study examines the use of eye tracking sensors as a means to identify children\u2019s behavior in attention-enhancement therapies. For this purpose, a set of data collected from 32 children with different attention skills is analyzed during their interaction with a set of puzzle games. The authors of this study hypothesize that participants with better performance may have quantifiably different eye-movement patterns from users with poorer results. The use of eye trackers outside the research community may help to extend their potential with available intelligent therapies, bringing state-of-the-art technologies to users. The use of gaze data constitutes a new information source in intelligent therapies that may help to build new approaches that are fully-customized to final users\u2019 needs. This may be achieved by implementing machine learning algorithms for classification. The initial study of the dataset has proven a 0.88 (\u00b10.11) classification accuracy with a random forest classifier, using cross-validation and hierarchical tree-based feature selection. Further approaches need to be examined in order to establish more detailed attention behaviors and patterns among children with and without attention problems.<\/jats:p>","DOI":"10.3390\/s150511092","type":"journal-article","created":{"date-parts":[[2015,5,12]],"date-time":"2015-05-12T11:05:31Z","timestamp":1431428731000},"page":"11092-11117","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":64,"title":["Assessing Visual Attention Using Eye Tracking Sensors in Intelligent Cognitive Therapies Based on Serious Games"],"prefix":"10.3390","volume":"15","author":[{"given":"Maite","family":"Frutos-Pascual","sequence":"first","affiliation":[{"name":"DeustoTech Life [eVIDA] Faculty of Engineering University of Deusto, Avda de las Universidades 24, Bilbao 48015, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9356-1186","authenticated-orcid":false,"given":"Begonya","family":"Garcia-Zapirain","sequence":"additional","affiliation":[{"name":"DeustoTech Life [eVIDA] Faculty of Engineering University of Deusto, Avda de las Universidades 24, Bilbao 48015, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2015,5,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1080\/00313830802497265","article-title":"The playing learning child: Towards a pedagogy of early childhood","volume":"52","author":"Samuelsson","year":"2008","journal-title":"Scand. 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