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- W2810007737 abstract "To minimize human errors (principal reasons for accidents in process industries) it is imperative to understand their cognitive workload, the excess of which is often a preliminary state leading to human errors. In this work, we have devised a methodology based on an eye tracking parameter—gaze entropy—to gauge the variation of cognitive work load on a control room operator. The study highlights the potential of gaze entropy in observing the variation of cognitive workload with learning. The patterns observed have a potential to minimize human errors and improve safety in process industries." @default.
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- W2810007737 date "2018-01-01" @default.
- W2810007737 modified "2023-10-16" @default.
- W2810007737 title "Towards Obviating Human Errors in Real-time through Eye Tracking" @default.
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- W2810007737 doi "https://doi.org/10.1016/b978-0-444-64235-6.50207-2" @default.
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