ABSTRACT
In training, task proficiency is typically assessed through relevant performance measures. Such measures provide information about how effectively the individual can perform the task, but they give no insight about cognitive efficiency. Neural signals may provide this information regarding a trainee’s task proficiency that performance measures alone cannot. The purpose of this study was to investigate patterns in neural activity that are indicative of task proficiency. Ten novice participants completed ten trials of a maneuvering task in a lifeboat simulator while their neural activity was recorded via electroencephalography (EEG). Power spectral features were used along with linear discriminant analysis to classify the data from pairs of adjacent trials. Repeated measures mixed model linear regression showed that, on average, the accuracy with which adjacent trials could be discriminated from each other decreased significantly over the course of training. The result indicates that with practice, the associated neural activity becomes more similar from trial to trial.
Acknowledgments
The authors would like to acknowledge Virtual Marine for their expert guidance and use of their lifeboat simulator.
Disclosure of potential conflicts of interest
The authors have no conflicts of interest to disclose.
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Notes on contributors
Rifat Biswas
Rifat Biswas was born in Dhaka, Bangladesh. He received a B.Sc. (electrical engineering) from Islamic University of Technology (IUT) in 2014 and an M.Eng. (electrical) from Memorial University of Newfoundland in 2018. His research area was focused on analysis of brain signals during VE-based training.
Brian Veitch
Brian Veitch teaches at Memorial University of Newfoundland, where he has been in the Faculty of Engineering & Applied Science since 1998. His research work focuses on the safety of people at work, especially those who work at sea.
Sarah D. Power
Sarah D. Power is an assistant professor in the Faculties of Engineering and Medicine at Memorial University of Newfoundland. She received a B.Eng. from Memorial in 2006, and an M.A.Sc. and Ph.D. (biomedical engineering) from the University of Toronto in 2008 and 2012. Her research focuses on brain-computer interfacing and neuroergonomics.