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Using Psychophysiological Sensors to Assess Mental Workload During Web Browsing

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 respo...

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Detalles Bibliográficos
Autores principales: Jimenez-Molina, Angel, Retamal, Cristian, Lira, Hernan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5855035/
https://www.ncbi.nlm.nih.gov/pubmed/29401688
http://dx.doi.org/10.3390/s18020458
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author Jimenez-Molina, Angel
Retamal, Cristian
Lira, Hernan
author_facet Jimenez-Molina, Angel
Retamal, Cristian
Lira, Hernan
author_sort Jimenez-Molina, Angel
collection PubMed
description 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%.
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spelling pubmed-58550352018-03-20 Using Psychophysiological Sensors to Assess Mental Workload During Web Browsing Jimenez-Molina, Angel Retamal, Cristian Lira, Hernan Sensors (Basel) Article 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%. MDPI 2018-02-03 /pmc/articles/PMC5855035/ /pubmed/29401688 http://dx.doi.org/10.3390/s18020458 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Jimenez-Molina, Angel
Retamal, Cristian
Lira, Hernan
Using Psychophysiological Sensors to Assess Mental Workload During Web Browsing
title Using Psychophysiological Sensors to Assess Mental Workload During Web Browsing
title_full Using Psychophysiological Sensors to Assess Mental Workload During Web Browsing
title_fullStr Using Psychophysiological Sensors to Assess Mental Workload During Web Browsing
title_full_unstemmed Using Psychophysiological Sensors to Assess Mental Workload During Web Browsing
title_short Using Psychophysiological Sensors to Assess Mental Workload During Web Browsing
title_sort using psychophysiological sensors to assess mental workload during web browsing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5855035/
https://www.ncbi.nlm.nih.gov/pubmed/29401688
http://dx.doi.org/10.3390/s18020458
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