An investigation of the effect of workload on ship engine room operators using fNIRS

• Published in: Ocean engineering 2024-10, Vol.310, p.118671, Article 118671
• Main Authors: Symes, Steve, Blanco-Davis, Eddie, Fairclough, Steve, Yang, Zaili, Wang, Jin, Shaw, Edward
• Format: Article
• Language: English
• Subjects: fNIRS; Human reliability assessment; Operator functional state; Simulator; Workload
• ISSN: 0029-8018
• DOI: 10.1016/j.oceaneng.2024.118671

This is an investigation into the Performance Shaping Factors (PSFs) associated with ship engine room operators. This study looks at the effect of workload. There is a large portion of human error associated with marine incidents. Human error may be considered as a result of additional supplementary tasks on top of an accustomed workload. The aim of this study is to evaluate the effect of workload on human performance. To achieve this, a TRANSAS simulator series 5000 was used to replicate a real scenario with the addition of workload as a PSF. Each participant engaged in a fault detection and correction task. 20 participants were used for the workload study; all 20 were trained for 3 h to use the engine room software interface. The participants then completed a 30-min ballasting task. During this interaction, 50% of the participants underwent a simulated scenario where the workload was increased. The other 50% were given a standard task. Functional near-infrared spectroscopy (fNIRS) was used to measure the participant's activation levels, more specifically from the dorsolateral prefrontal cortex (DLPFC) region of the cerebrum. The results showed an increase in activation of the DLPFC during each phase of the task, this trend was magnified by the addition of increased workload. The results are discussed with respect to human performance during varying workload. From the results of this study, a human classification performance model was developed. This model can be used by the maritime industry to better evaluate and understand human error causation. •By monitoring brain activity, researchers gain objective insights into the cognitive demands placed on engine room personnel during various operational scenarios.•Understanding workload levels allows for better task allocation, risk mitigation strategies, and potentially improved bridge-engine room communication, ultimately enhancing crew performance and safety.•The findings can inform the design of future engine room interfaces and automation systems to minimize cognitive load and optimize brain-computer interface interaction.