New human psycho-physiological workload monitoring model

Due to the important role of the air traffic control operator (ATOC), where high risk is involved, it is imperative to observe their cognitive states when they are performing their tasks. This project aims to firstly design an ergonomic electroencephalogram (EEG) device with a reduced number of chan...

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Bibliographic Details
Main Author: Kirana, Dennis Febrian
Other Authors: Lye Sun Woh
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/150822
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Institution: Nanyang Technological University
Language: English
Description
Summary:Due to the important role of the air traffic control operator (ATOC), where high risk is involved, it is imperative to observe their cognitive states when they are performing their tasks. This project aims to firstly design an ergonomic electroencephalogram (EEG) device with a reduced number of channels for the use of ATOC in their daily jobs that can measure the attentive levels of the user and secondly to examine whether different cognitive states of the user can be observed in different conditions. This project conducted experiments with varying conditions to obtain the different cognitive states of participants with the use of an EEG headgear device. After the raw data is obtained, processing the data is done, from cleaning, filtering, artifact removal and estimating power spectral density (PSD), the spectral power of the different times and conditions are obtained. Data analysis through tests such as single factor analysis of variance (ANOVA) test as well as comparison of PSD is done for the different participants. It is shown that there are channels which measures similar EEG signals, and a reduced number of probes can be obtained while still being able to differentiate the user’s states of attentive and non-attentive. The results and analysis also show good justification in differentiating different spectral powers of cognitive states such as talking and keeping quiet as well as when questions are prompted. All this data and analysis will aid the people who oversee ATOCs, by being able to keep track of their attention and the varying cognitive states.