Abstract
The measurement of fatigue and drowsiness is a challenging job in today’s world. EOG signal analysis is a purely noninvasive method of evaluating the movement of eyeball in the horizontal and vertical direction. It is a feasible and reliable technique in comparison to the other physiological signal based technique to determine and quantify the fatigue and drowsiness of the drivers/operators. For this study, data from ten participants who are physically sound are taken. Three different frequency of visual cue and different time slots of a day has been considered and three parameters like cornea pace, moving window sample entropy and moving window fuzzy entropy are evaluated on the basis of the real time signal. The experimental results show that with the gradual enhancement of cue frequency in afternoon as well as the night shift the complexity of the horizontal data and the complexity of the vertical data increases. The cornea pace is also reduces considerably with the fatigue. The dynamics of cornea pace usually show the speed at which the eye ball follow a certain specific object. It is concluded that the fatigue and drowsiness increase with muscle stress, sleep deprivation, and the gap between the two sleep cycles.
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Das, A.K., Kumar, P., Halder, S., Banerjee, A., Tibarewala, D.N. (2020). An Experimental Paradigm for Evaluation of Entropy and Pace Based Ocular Parameters for Detection of Fatigue and Drowsiness. In: Dawn, S., Balas, V., Esposito, A., Gope, S. (eds) Intelligent Techniques and Applications in Science and Technology. ICIMSAT 2019. Learning and Analytics in Intelligent Systems, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-030-42363-6_75
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DOI: https://doi.org/10.1007/978-3-030-42363-6_75
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