Innovative Brain-Computer Interface based on motor cortex activity to detect accidental awareness during general anesthesia

Abstract : Accidental Awareness during General Anesthesia (AAGA) occurs in 1-2% of high-risk practice patients and is responsible for severe psychological trauma, termed post-traumatic stress disorder (PTSD). Currently, monitoring techniques have limited accuracy in predicting or detecting AAGA. Since the first reflex of a patient experiencing AAGA is to move, a passive Brain-Computer Interface (BCI) based on the detection of an intention of movement would be conceivable to alert the anesthetist and prevent this phenomenon. However, the way in which the propofol (an anesthetic drug commonly used for inducing and maintaining general anesthesia) affects the motor brain activity and is reflected by the electroencephalo-graphic (EEG) signal has been poorly investigated and is not clearly understood. The goal of this forward-looking study is to investigate the motor activity behavior with step-wise increase of propofol doses in 4 healthy subjects and provide a proof of concept for such an innovative BCI.
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Submitted on : Thursday, June 27, 2019 - 12:15:11 PM
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Sébastien Rimbert, Philippe Guerci, Nathalie Gayraud, Claude Meistelman, Laurent Bougrain. Innovative Brain-Computer Interface based on motor cortex activity to detect accidental awareness during general anesthesia. IEEE SMC 2019 - IEEE International Conference on Systems, Man, and Cybernetics, Oct 2019, Bari, Italy. ⟨hal-02166934⟩

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