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安全关键任务中的神经工效学注意力评估:在新型任务嵌入反应时范式中对脑电图指标和主观指标的验证

Neuroergonomic Attention Assessment in Safety-Critical Tasks: EEG Indices and Subjective Metrics Validation in a Novel Task-Embedded Reaction Time Paradigm.

作者信息

Bjegojević Bojana, Pušica Miloš, Gianini Gabriele, Gligorijević Ivan, Cromie Sam, Leva Maria Chiara

机构信息

Human Factors in Safety and Sustainability (HFISS), Technological University Dublin, D07 EWV4 Dublin, Ireland.

Centre for Innovative Human Systems (CIHS), Trinity College Dublin, D02 PN40 Dublin, Ireland.

出版信息

Brain Sci. 2024 Oct 7;14(10):1009. doi: 10.3390/brainsci14101009.

DOI:10.3390/brainsci14101009
PMID:39452023
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11506387/
Abstract

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. 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. 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. 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.

摘要

本研究填补了安全关键任务中神经工效学注意力评估方法指南的空白,重点验证脑电图指标,包括参与指数(EI)和β/α比率,以及主观评分。开发了一种新颖的任务嵌入反应时范式,以评估这些指标在更自然的多任务环境中对动态注意力需求的敏感性。通过在NASA MATB-II任务中通过改变次要任务来操纵注意力水平,同时保持主要反应时任务一致,本研究成功证明了该范式的有效性。结果表明,β/α比率和EI均对注意力需求的变化敏感,其中β/α对注意力的动态变化反应更灵敏,而EI更多地反映了维持表现所需的总体努力,尤其是在保持注意力具有挑战性的情况下。通过整合绩效指标、脑电图测量和主观评估来预测注意力 lapses 的可能性得到了证明,从而对多任务场景中注意力的动态波动有了更细致入微的理解,模拟了现实世界中安全关键任务中的情况。这些发现为推进准确监测注意力波动并降低关键场景(如火车驾驶或自动驾驶汽车操作)中的风险的方法奠定了基础,在这些场景中保持高度注意力至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e43/11506387/0e495794528f/brainsci-14-01009-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e43/11506387/2c6dc8d3f520/brainsci-14-01009-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e43/11506387/f86350db1096/brainsci-14-01009-g009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e43/11506387/e17f0d37a550/brainsci-14-01009-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e43/11506387/be1cca75bb26/brainsci-14-01009-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e43/11506387/263310d6f471/brainsci-14-01009-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e43/11506387/ff77414812cf/brainsci-14-01009-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e43/11506387/2c6dc8d3f520/brainsci-14-01009-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e43/11506387/f86350db1096/brainsci-14-01009-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e43/11506387/3caacc92819a/brainsci-14-01009-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e43/11506387/9dcda4aaa6a2/brainsci-14-01009-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e43/11506387/0e495794528f/brainsci-14-01009-g013.jpg

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Front Neuroergon. 2020 Oct 27;1:583733. doi: 10.3389/fnrgo.2020.583733. eCollection 2020.
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