Design and preliminary study of a neurofeedback protocol to self-regulate an EEG marker of drowsiness

Abstract : Neurofeedback (NF) consists in using electroencephalographic (EEG) measurements to guide users to perform a cognitive learning using information coming from their own brain activity, by means of a real-time sensory feedback (e.g., visual or auditory). Many NF approaches have been studied to improve atten-tional abilities, notably for attention deficit hyper activity disorder. However, to our knowledge, no NF solution has been proposed to specifically reduce drowsiness. Thus, we propose an EEG-NF solution to train users to self-regulate an EEG marker of drowsiness, and evaluate it with a preliminary study. Results with five healthy subjects showed that three of them could learn to self-regulate this EEG marker with a relatively short number of NF sessions (up to 8 sessions of 40 min). Clinical trials with sleep-deprived subjects should begin in 2019 to study possible cognitive and clinical benefits of this self-regulation. This NF solution implementation is available for free, with the OpenViBE platform, under the AGPL-3.0 license.
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Submitted on : Thursday, May 16, 2019 - 9:57:19 AM
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Thibaut Monseigne, Fabien Lotte, Stéphanie Bioulac, Pierre Philip, Jean-Arthur Micoulaud-Franchi. Design and preliminary study of a neurofeedback protocol to self-regulate an EEG marker of drowsiness. Graz BCI Conference - 8th Graz Brain-Computer Interface Conference 2019, Sep 2019, Graz, Austria. ⟨hal-02130755⟩

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