Neuroergonomic Attention Assessment in Safety-Critical Tasks: EEG Indices and Subjective Metrics Validation in a Novel Task-Embedded Reaction Time Paradigm
<b>Background/Objectives:</b> This study addresses the gap in methodological guidelines for neuroergonomic attention assessment in safety-critical tasks, focusing on validating EEG indices, including the engagement index (EI) and beta/alpha ratio, alongside subjective ratings. <b>Methods:</b> A novel task-embedded reaction time paradigm was developed to evaluate the sensitivity of these metrics to dynamic attentional demands in a more naturalistic multitasking context. By manipulating attention levels through varying secondary tasks in the NASA MATB-II task while maintaining a consistent primary reaction-time task, this study successfully demonstrated the effectiveness of the paradigm. <b>Results:</b> Results indicate that both the beta/alpha ratio and EI are sensitive to changes in attentional demands, with beta/alpha being more responsive to dynamic variations in attention, and EI reflecting more the overall effort required to sustain performance, especially in conditions where maintaining attention is challenging. <b>Conclusions:</b> The potential for predicting the attention lapses through integration of performance metrics, EEG measures, and subjective assessments was demonstrated, providing a more nuanced understanding of dynamic fluctuations of attention in multitasking scenarios, mimicking those in real-world safety-critical tasks. These findings provide a foundation for advancing methods to monitor attention fluctuations accurately and mitigate risks in critical scenarios, such as train-driving or automated vehicle operation, where maintaining a high attention level is crucial.
Authors
- Miloš Pušica (ORCID: https://orcid.org/0009-0003-4522-6222)
- Sam Cromie (ORCID: https://orcid.org/0000-0001-5023-0435)
- Bojana Bjegojević (ORCID: https://orcid.org/0000-0002-8421-5572)
- Gabriele Gianini (ORCID: https://orcid.org/0000-0001-5186-0199)
- Maria Chiara Leva (ORCID: https://orcid.org/0000-0002-6770-8332)
- Ivan Gligorijević
Institutions
- Trinity College Dublin (IE)
- Technological University Dublin (IE)
- University of Milano-Bicocca (IT)
Publication Details
- Journal
- Brain Sciences
- Published
- 2024-10-07
- DOI
- https://doi.org/10.3390/brainsci14101009
- Citations
- 5
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 3.22