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Correlation between Situational Awareness and EEG signals

Kästle, JL; Anvari, B; Krol, J; Wurdemann, H; (2021) Correlation between Situational Awareness and EEG signals. Neurocomputing , 432 pp. 70-79. 10.1016/j.neucom.2020.12.026. Green open access

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Abstract

An important aspect in safety–critical domains is Situational Awareness (SA) where operators consolidate data into an understanding of the situation that needs to be updated dynamically as the situation changes over time. Among existing measures of SA, only physiological measures can assess the cognitive processes associated with SA in real-time. Some studies showed promise in detecting cognitive states associated with SA in complex tasks using brain signals (e.g. electroencephalogram/EEG). In this paper, an analytical methodology is proposed to identify EEG signatures associated with SA on various regions of the brain. A new data set from 32 participants completing the SA test in the PEBL is collected using a 32-channel dry-EEG headset. The proposed method is tested on the new data set and a correlation is identified between the frequency bands of b (12 - 30 Hz) and c (30 - 45 Hz) and SA. Also, activation of neurons in the left and right hemisphere of the parietal and temporal lobe is observed. These regions are responsible for the visuo-spatial ability and memory and reasoning tasks. Among the presented results, the highest achieved accuracy on test data is 67%.

Type: Article
Title: Correlation between Situational Awareness and EEG signals
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neucom.2020.12.026
Publisher version: https://doi.org/10.1016/j.neucom.2020.12.026
Language: English
Additional information: Copyright © 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Situational Awareness, Electroencephalograph (EEG), Psychology Experiment Building Language (PEBL) test, Random Forests, Decision trees, Brain computer interface
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering
URI: https://discovery.ucl.ac.uk/id/eprint/10118294
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