A real time neurophysiological framework for general monitoring awareness of air traffic controllers

With the increasing traffic volume, air traffic controllers (ATCos) highly efficient performance plays an essential part in ensuring the safety and managing within limited manpower and resources. To ensure the performance, one way is to perform situation awareness (SA) examination. However, the know...

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Bibliographic Details
Main Authors: Yuvaraj, Rajamanickam, Lye, Sun Woh, Wee, Hong Jie
Other Authors: School of Mechanical and Aerospace Engineering
Format: Conference or Workshop Item
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/147501
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Institution: Nanyang Technological University
Language: English
Description
Summary:With the increasing traffic volume, air traffic controllers (ATCos) highly efficient performance plays an essential part in ensuring the safety and managing within limited manpower and resources. To ensure the performance, one way is to perform situation awareness (SA) examination. However, the known SA methods (such as text query) are either subjective or inapplicable in a practical scenario. Therefore, the use of physiological signals is becoming popular. In this work, a real time monitoring approach is proposed to assess a general monitoring awareness while looking at the events happening at the radar display during air traffic control (ATC), using neurophysiological measures taken from electroencephalogram (EEG) signals along with eye-tracking metrics such as eye fixation count and duration. Seven university engineering students participated in the attentive and non-attentive radar monitoring activities. The preliminary experimental results revealed that the real-time data of EEG, average fixation count, and fixation duration highlight distinct differences in levels between attentive and non-attentive monitoring activities (individual and collective). Also, the cognitive resource required for air traffic management (ATM) monitoring is relatively high. Such measures can be used as complementary data sets to gauge and validate an ATCos general SA