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Open AccessArticle

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

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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