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Sensors 2018, 18(2), 458; https://doi.org/10.3390/s18020458

Using Psychophysiological Sensors to Assess Mental Workload During Web Browsing

1
Department of Industrial Engineering, Faculty of Physical and Mathematical Sciences, University of Chile, Santiago 8370456, Chile
2
Department of Electrical Engineering, Faculty of Physical and Mathematical Sciences, University of Chile, Santiago 8370448, Chile
*
Author to whom correspondence should be addressed.
Received: 4 December 2017 / Revised: 7 January 2018 / Accepted: 22 January 2018 / Published: 3 February 2018
(This article belongs to the Special Issue Advanced Physiological Sensing)
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Abstract

Knowledge of the mental workload induced by a Web page is essential for improving users’ browsing experience. However, continuously assessing the mental workload during a browsing task is challenging. To address this issue, this paper leverages the correlation between stimuli and physiological responses, which are measured with high-frequency, non-invasive psychophysiological sensors during very short span windows. An experiment was conducted to identify levels of mental workload through the analysis of pupil dilation measured by an eye-tracking sensor. In addition, a method was developed to classify mental workload by appropriately combining different signals (electrodermal activity (EDA), electrocardiogram, photoplethysmo-graphy (PPG), electroencephalogram (EEG), temperature and pupil dilation) obtained with non-invasive psychophysiological sensors. The results show that the Web browsing task involves four levels of mental workload. Also, by combining all the sensors, the efficiency of the classification reaches 93.7%. View Full-Text
Keywords: psychophysiological sensors; mental workload; Web browsing tasks; machine learning psychophysiological sensors; mental workload; Web browsing tasks; machine learning
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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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Jimenez-Molina, A.; Retamal, C.; Lira, H. Using Psychophysiological Sensors to Assess Mental Workload During Web Browsing. Sensors 2018, 18, 458.

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