Towards a Novel Monitor of Intraoperative Awareness: Selecting Paradigm Settings for a Movement-Based Brain-Computer Interface

Yvonne M Blokland, Jason D R Farquhar, Jo Mourisse, Gert J Scheffer, Jos G C Lerou and Jörgen Bruhn

PLOS ONE, 2012, vol. 7, issue 9, 1-9

Abstract: During 0.1–0.2% of operations with general anesthesia, patients become aware during surgery. Unfortunately, pharmacologically paralyzed patients cannot seek attention by moving. Their attempted movements may however induce detectable EEG changes over the motor cortex. Here, methods from the area of movement-based brain-computer interfacing are proposed as a novel direction in anesthesia monitoring. Optimal settings for development of such a paradigm are studied to allow for a clinically feasible system. A classifier was trained on recorded EEG data of ten healthy non-anesthetized participants executing 3-second movement tasks. Extensive analysis was performed on this data to obtain an optimal EEG channel set and optimal features for use in a movement detection paradigm. EEG during movement could be distinguished from EEG during non-movement with very high accuracy. After a short calibration session, an average classification rate of 92% was obtained using nine EEG channels over the motor cortex, combined movement and post-movement signals, a frequency resolution of 4 Hz and a frequency range of 8–24 Hz. Using Monte Carlo simulation and a simple decision making paradigm, this translated into a probability of 99% of true positive movement detection within the first two and a half minutes after movement onset. A very low mean false positive rate of

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0044336

DOI: 10.1371/journal.pone.0044336

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