{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T03:16:09Z","timestamp":1773890169532,"version":"3.50.1"},"reference-count":104,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2018,2,3]],"date-time":"2018-02-03T00:00:00Z","timestamp":1517616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"CONICYT FONDECYT program","award":["11130252"],"award-info":[{"award-number":["11130252"]}]},{"name":"Instituto Sistemas Complejos de Ingenier\u00eda\u201d (CONICYT: Proyecto Basal)","award":["FBO16"],"award-info":[{"award-number":["FBO16"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Knowledge of the mental workload induced by a Web page is essential for improving users\u2019 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%.<\/jats:p>","DOI":"10.3390\/s18020458","type":"journal-article","created":{"date-parts":[[2018,2,5]],"date-time":"2018-02-05T04:29:42Z","timestamp":1517804982000},"page":"458","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":80,"title":["Using Psychophysiological Sensors to Assess Mental Workload During Web Browsing"],"prefix":"10.3390","volume":"18","author":[{"given":"Angel","family":"Jimenez-Molina","sequence":"first","affiliation":[{"name":"Department of Industrial Engineering, Faculty of Physical and Mathematical Sciences, University of Chile, Santiago 8370456, Chile"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cristian","family":"Retamal","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Faculty of Physical and Mathematical Sciences, University of Chile, Santiago 8370448, Chile"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hernan","family":"Lira","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, Faculty of Physical and Mathematical Sciences, University of Chile, Santiago 8370456, Chile"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,2,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Landauer, T. 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