Mental Workload Classification By Eye Movements In Visual Search Tasks

This paper presents a method to objectively evaluate mental workload by analyzing the changes of eye movements characteristics in different visual search tasks. Eye movements data were collected by the eye tracking device called Eye Tracking Core+ while subjects were performing four different visual...

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Published in2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) pp. 29 - 33
Main Authors Pang, Liping, Fan, Yurong, Deng, Ye, Wang, Xin, Wang, Tianbo
Format Conference Proceeding
LanguageEnglish
Published IEEE 17.10.2020
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DOI10.1109/CISP-BMEI51763.2020.9263668

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Summary:This paper presents a method to objectively evaluate mental workload by analyzing the changes of eye movements characteristics in different visual search tasks. Eye movements data were collected by the eye tracking device called Eye Tracking Core+ while subjects were performing four different visual search tasks produced by NASA's Multi-Attribute Task Battery (MATB) on the screen of computer. By varying the difficulty of visual search tasks, the eye movements were measured to examine whether they could be used to classify the mental workload. As a result, the five indexes (Saccades Amplitude, Saccades Velocity, Fixation Duration, Blink Duration and Pupil Diameter) showed significant differences under low and high workload of visual search tasks. Moreover, with the increase of task workload, Saccades Amplitude, Saccades Velocity, and Blink Duration decreased significantly, while Fixation Duration and Pupil Diameter increased gradually.
DOI:10.1109/CISP-BMEI51763.2020.9263668