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Using theta and alpha band power to assess cognitive workload in multitasking environments

Abstract : Cognitive workload is of central importance in the fields of human factors and ergonomics. A reliable measurement of cognitive workload could allow for improvements in human machine interface designs and increase safety in several domains. At present, numerous studies have used electroencephalography (EEG) to assess cognitive workload, reporting the rise in cognitive workload to be associated with increases in theta band power and decreases in alpha band power. However, results have been inconsistent with some failing to reach the required level of significance. We hypothesized that the lack of consistency could be related to individual differences in task performance and/or to the small sample sizes in most EEG studies. In the present study we used EEG to assess the increase in cognitive workload occurring in a multitasking environment while taking into account differences in performance. Twenty participants completed a task commonly used in airline pilot recruitment, which included an increasing number of concurrent sub-tasks to be processed from one to four. Subjective ratings, performances scores, pupil size and EEG signals were recorded. Results showed that increases in EEG alpha and theta band power reflected increases in the involvement of cognitive resources for the completion of one to three subtasks in a multitasking environment. These values reached a ceiling when performances dropped. Consistent differences in levels of alpha and theta band power were associated to levels of task performance: highest performance was related to lowest band power.
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https://hal-enac.archives-ouvertes.fr/hal-01626535
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Soumis le : lundi 30 octobre 2017 - 21:13:47
Dernière modification le : mercredi 17 novembre 2021 - 12:32:05

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Sébastien Puma, Nadine Matton, Pierre-Vincent Paubel, Éric Raufaste, Radouane El-Yagoubi. Using theta and alpha band power to assess cognitive workload in multitasking environments. International Journal of Psychophysiology, Elsevier, 2018, 123 (01-2018), pp.111-120. ⟨10.1016/j.ijpsycho.2017.10.004⟩. ⟨hal-01626535⟩

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