2022
DOI: 10.1016/j.apergo.2022.103829
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Scan-based eye tracking measures are predictive of workload transition performance

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Cited by 4 publications
(2 citation statements)
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“…This was done by analyzing performance and eye tracking data within growth curve modeling. Our results suggested that individual's performance differed across and within all three workload transition rates and that visual attention allocation patterns started to explain those differences in performance trends (details in Devlin et al, 2022Devlin et al, , 2023). I will discuss the implications of these findings, especially as it pertains to designing future control systems.…”
Section: Distribution Statement a Approved For Public Release Distrib...mentioning
confidence: 66%
“…This was done by analyzing performance and eye tracking data within growth curve modeling. Our results suggested that individual's performance differed across and within all three workload transition rates and that visual attention allocation patterns started to explain those differences in performance trends (details in Devlin et al, 2022Devlin et al, , 2023). I will discuss the implications of these findings, especially as it pertains to designing future control systems.…”
Section: Distribution Statement a Approved For Public Release Distrib...mentioning
confidence: 66%
“…For example, the concept of visual entropy was introduced to measure the size of image information and the sensitivity of the human visual system to images [91]. Devlin et al [92] used gaze entropy as an important predictive indicator of workload. Zhao et al [93] determined the threshold values for discriminating fatigue driving behavior indicators under different road line shapes, and established a comprehensive fatigue driving discrimination model based on various driving behavior indicators and threshold values.…”
Section: Transportation Systemmentioning
confidence: 99%