Abstract
Vigilance is important for jobs requiring sustained attention for prolonged times, especially in this century where terrorism poses a challenge to the world. This research investigates a sensorised approach to objectively evaluate vigilance levels to maintain optimal work performance. We conducted two experiments on 25 subjects using low cost EEG and eye tracker. The first experiment identified the optimal working conditions for the selected eye tracker. By applying these conditions in vigilance testing, both accuracy and precision of the eye tracker achieved above 90%. Vigilance level was observed to have decreased over time by analysing eye gaze and using reaction time in quantifying vigilance level. These findings were supported by EEG band power features; showing a decrease in frontal asymmetry index corresponding to vigilance level. The increased theta and decreased beta powers in temporal lobes were identified; where of high beta reflects alertness while high theta results drowsiness. From our investigation, the decline in vigilance level corresponds to an increase in reaction time, blink rates, decrease in frontal alpha asymmetry index and change in beta and theta bands. With the sensorised objective measures of vigilance levels, appropriate countermeasures can be taken when respondents’ vigilance level is low to alleviate these undesirable and unproductive states.
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Acknowledgements
Firstly, we are particularly grateful for the assistance given by 2 NTU undergraduate students, Nageshwari and Jamie Yap Yi Qi, for helping us with the data analysis. We would also like to express our appreciation to our teacher-mentor, Mr. Ang Joo Liak, for helping us with numerous administrative tasks during this entire journey. Last but not least, we would like to acknowledge with much appreciation to our school’s (NYGH) ICT department, for loaning us required equipment for experiments.
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Xue, Y., Tan, W., Ang, J.N.S., Aung, A.P.W. (2019). Investigation of Low Cost Eye Tracker and EEG for Objectively Assessing Vigilance Level. In: Guo, H., Ren, H., Bandla, A. (eds) IRC-SET 2018. Springer, Singapore. https://doi.org/10.1007/978-981-32-9828-6_6
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DOI: https://doi.org/10.1007/978-981-32-9828-6_6
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