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Eye tracking and EEG features for salient web object identification

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6 Citas (Scopus)

Resumen

We propose a biological-based feature comparison for identifying salient Web objects. We compare several features extracted from eye tracking and EEG data with a baseline given by mean fixation impact introduced by Buscher. For this, we performed an experiment with 20 healthy subjects in which gaze position, pupil size and brain activity were recorded while browsing in a Web site adaptation. Our results show that there are EEG features that could be related to Web user attention in objects. In particular the Gamma Band RMS and the EEG Variance indicate that the longer subjects view a web object (more attention), the less brain signal disturbance appears. We also discarded pupil size features due to low correlation with baseline. These results suggest that EEG features could be used to identify salient objects without using the time users spent on them as done in previous methodologies.

Idioma originalInglés
Título de la publicación alojadaBrain Informatics and Health - 8th International Conference, BIH 2015, Proceedings
EditoresYike Guo Y., Sean Hill S., Karl Friston, Hanchuan Peng, Aldo Faisal A.
EditorialSpringer Verlag
Páginas3-12
Número de páginas10
ISBN (versión impresa)9783319233437
DOI
EstadoPublicada - 2015
Publicado de forma externaSí
Evento8th International Conference on Brain Informatics and Health, BIH 2015 - London, Reino Unido
Duración: 30 ago 2015 → 2 sept 2015

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen9250
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia8th International Conference on Brain Informatics and Health, BIH 2015
País/TerritorioReino Unido
CiudadLondon
Período30/08/15 → 2/09/15

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