EEG-based mental workload and stress recognition of crew members in maritime virtual simulator : a case study

• Main Authors: Liu, Yisi, Subramaniam, Salem Chandrasekaran Harihara, Sourina, Olga, Liew, Serene Hui Ping, Krishnan, Gopala, Konovessis, Dimitrios, Ang, Hock Eng
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2021
• Subjects: Engineering::Maritime studies; Human Factors; Electroencephalography
• Online Access: https://hdl.handle.net/10356/145971
• Institution: Nanyang Technological University

Many studies have shown that the majority of maritime accidents/incidents are attributed to human errors as the initiating cause. Efforts have been made to study human factors that can result in a safer maritime transportation. Among all techniques, Electroencephalogram (EEG) has the advantages such as high time resolution, possibility to continuously monitor brain states with high accuracy, recognition of human mental workload, emotion, stress, vigilance, etc. In this paper, we designed and carried out an experiment to collect the EEG signals to study stress and sharing of the mental workload among crew members during collaboration tasks performance on the ship's bridge virtual simulator. Four maritime trainees were monitored in the experiment. Each of them had a role such as an officer on watch, captain, pilot, or steersman. The results show that the captain had the highest stress and workload. However, the other three trainees experienced low workload and stress due to shared work and responsibility. The EEG is a promising evaluation tool to be used in the human factors study in the maritime domain.