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Tracking drivers’ minds: Continuous evaluation of mental load and cognitive processing in a realistic driving simulator scenario by means of the EEG
Driving safety strongly depends on the driver's mental states and attention to the driving situation. Previous studies demonstrate a clear relationship between EEG measures and mental states, such as alertness and drowsiness, but often only map their mental state for a longer period of time. In...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10395282/ https://www.ncbi.nlm.nih.gov/pubmed/37539180 http://dx.doi.org/10.1016/j.heliyon.2023.e17904 |
Sumario: | Driving safety strongly depends on the driver's mental states and attention to the driving situation. Previous studies demonstrate a clear relationship between EEG measures and mental states, such as alertness and drowsiness, but often only map their mental state for a longer period of time. In this driving simulation study, we exploit the high temporal resolution of the EEG to capture fine-grained modulations in cognitive processes occurring before and after eye activity in the form of saccades, fixations, and eye blinks. A total of 15 subjects drove through an approximately 50-km course consisting of highway, country road, and urban passages. Based on the ratio of brain oscillatory alpha and theta activity, the total distance was classified into 10-m-long sections with low, medium, and high task loads. Blink-evoked and fixation-evoked event-related potentials, spectral perturbations, and lateralizations were analyzed as neuro-cognitive correlates of cognition and attention. Depending on EEG-based estimation of task load, these measures showed distinct patterns associated with driving behavior parameters such as speed and steering acceleration and represent a temporally highly resolved image of specific cognitive processes during driving. In future applications, combinations of these EEG measures could form the basis for driver warning systems which increase overall driving safety by considering rapid fluctuations in driver's attention and mental states. |
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