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Monitoring-pilot-trainees-cognitive-control-under-a-simulator-based-training-process
forked from rachelzmt/Monitoring-pilot-trainees-cognitive-control-under-a-simulator-based-training-process
DOI
10.12751/g-node.dh7zhl
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The present research aims to investigate changes in trainees’ cognitive control levels during a pilot training process while they underwent basic flight maneuvers. EEG microstate analysis was applied together with spectral power features to quantitatively monitor trainees’ cognitive control under varied flight tasks during different training sessions. Comparisons were conducted between two types of tasks and among different training stages in terms of trainees' cognitive control.

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README.md

Monitoring-pilot-trainees-cognitive-control-under-a-simulator-based-training-process

Description

This repository contains software for analyzing EEG data to investigate changes in cognitive control levels in pilot trainees during a training process involving basic flight maneuvers. The code is specifically tailored for applying EEG microstate analysis and spectral power feature extraction to monitor cognitive control under various flight tasks across multiple training sessions.

Data format

The software is designed to work with EEG data recorded using the 64-channel Biosemi system. The data should contain 64 channels labeled appropriately according to the Biosemi convention. Please ensure the data has undergone basic preprocessing before using it with this software.

Installation and Requirements

The code in this repository was developed and tested using Python 3.8. It is recommended to use a similar or newer version to ensure compatibility.

Dependencies

MNE: For EEG data handling and preprocessing. NumPy: For numerical operations. SciPy: For statistical analysis. Matplotlib: For visualizing EEG data.

datacite.yml
Title Monitoring pilot trainees’ cognitive control under a simulator-based training process with EEG microstate analysis
Authors Zhao,Mengting;Concordia University
Jia,Wenjun;Concordia University
Jennings,Sion;National Research Council of Canada
Law,Andrew;National Research Council of Canada
Bourgon,Alain;CAE Inc.
Su,Chang;Concordia University
Larose,Marie-Helene;Marinvent Corporation
Grenier,Hugh;CAE Inc.
Bowness,David;CAE Inc.
Zeng,Yong;Concordia University
Description The present codes aim to monitor variations in pilot trainees’ cognitive control during a pilot training process using EEG microstate analysis and traditional bandpower.
License Creative Commons CC0 1.0 Public Domain Dedication (https://creativecommons.org/publicdomain/zero/1.0/)
References
Funding NSERC CRD project
Mitacs Accelerate program
Keywords Cognitive control
pilot training
EEG microstate analysis
Resource Type Software