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Sensors 2015, 15(5), 11092-11117;

Assessing Visual Attention Using Eye Tracking Sensors in Intelligent Cognitive Therapies Based on Serious Games

DeustoTech Life [eVIDA] Faculty of Engineering University of Deusto, Avda de las Universidades 24, Bilbao 48015, Spain
Author to whom correspondence should be addressed.
Academic Editor: Gianluca Paravati
Received: 24 February 2015 / Revised: 22 April 2015 / Accepted: 27 April 2015 / Published: 12 May 2015
(This article belongs to the Special Issue HCI In Smart Environments)
Full-Text   |   PDF [19429 KB, uploaded 13 May 2015]


This study examines the use of eye tracking sensors as a means to identify children’s 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’ needs. This may be achieved by implementing machine learning algorithms for classification. The initial study of the dataset has proven a 0.88 (±0.11) 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. View Full-Text
Keywords: eye tracker; attention; intelligent therapies; serious games; children eye tracker; attention; intelligent therapies; serious games; children
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Frutos-Pascual, M.; Garcia-Zapirain, B. Assessing Visual Attention Using Eye Tracking Sensors in Intelligent Cognitive Therapies Based on Serious Games. Sensors 2015, 15, 11092-11117.

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