Investigation of an EEG-based Indicator of Skill Acquisition as Novice Participants Practice a Lifeboat Maneuvering Task in a Simulator. Issue 8 (8th May 2020)

• Record Type: Journal Article
• Authors: Biswas, Rifat; Veitch, Brian; Power, Sarah D.
• Is Part Of: International journal of human-computer interaction. Volume 36:Issue 8(2020)
• Page Start: 777
• Page End: 787
• Publication Date: 2020-05-08
• Subjects: Human-computer interaction -- Periodicals; 004.01905
• DOI: 10.1080/10447318.2019.1687235
• Languages: English
• ISSNs: 1044-7318

Abstract

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.