Assessing visual attention using eye tracking sensors in intelligent cognitive therapies based on serious games
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Fecha
2015-05-12
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MDPI AG
Resumen
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.
Palabras clave
Attention
Children
Eye tracker
Intelligent therapies
Serious games
Children
Eye tracker
Intelligent therapies
Serious games
Descripción
Materias
Cita
Frutos-Pascual, M., & Garcia-Zapirain, B. (2015). Assessing visual attention using eye tracking sensors in intelligent cognitive therapies based on serious games. Sensors (Switzerland), 15(5), 11092-11117. https://doi.org/10.3390/S150511092