Abstract
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.
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Slanzi, G., Aracena, C., Velásquez, J.D. (2015). Eye Tracking and EEG Features for Salient Web Object Identification. In: Guo, Y., Friston, K., Aldo, F., Hill, S., Peng, H. (eds) Brain Informatics and Health. BIH 2015. Lecture Notes in Computer Science(), vol 9250. Springer, Cham. https://doi.org/10.1007/978-3-319-23344-4_1
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DOI: https://doi.org/10.1007/978-3-319-23344-4_1
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