EEG-based mental workload recognition during multi-tasking scenarios: the role of resting-state normalization and brain region of EEG features.

IF 2.8 3区工程技术 Q3 ENGINEERING, INDUSTRIAL

Ergonomics Pub Date : 2026-10-02 DOI:10.1080/00140139.2026.2741275

Yuchen Ji, Zongqi Liang, Jiaqi Huang, Da Tao

引用次数: 0

Abstract

EEG-based mental workload (MWL) recognition is challenged by inter-individual variability and limited model interpretability. This study investigated MWL recognition in long-term multi-tasking scenarios using resting-state EEG normalisation and regional feature analysis. Participants performed multi-tasking operations at three difficulty levels, while resting-state and task-state EEG, behavioural performance, and NASA-TLX ratings were collected. The best whole-brain model achieved 93.78% ± 0.45% accuracy under standard normalisation, while the parietal configuration retained substantial recognition capability with fewer electrodes. Resting-state normalisation changed EEG feature-importance patterns, but its effects on classification were classifier-dependent rather than uniformly beneficial. SHAP analysis identified prominent frontal and parietal contributions. The findings support interpretable and lightweight EEG-based MWL monitoring in complex operational environments.

查看原文本刊更多论文

多任务情景下基于脑电图的精神工作量识别：静息状态归一化与脑电特征脑区的作用。

基于脑电图的心智负荷识别受到个体间差异性和模型可解释性的限制。本研究采用静息状态EEG归一化和区域特征分析的方法研究了长期多任务场景下的MWL识别。参与者在三个难度等级下进行多任务操作，同时收集静息状态和任务状态脑电图、行为表现和NASA-TLX评分。在标准归一化下，最佳全脑模型的准确率为93.78%±0.45%，而顶叶构型在较少电极的情况下仍具有较强的识别能力。静息状态归一化改变了脑电特征重要性模式，但其对分类的影响是分类器依赖的，而不是一致的有益。SHAP分析发现了突出的额叶和顶叶贡献。研究结果支持在复杂的操作环境中进行可解释和轻量级的基于脑电图的MWL监测。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Ergonomics 工程技术-工程：工业

CiteScore

4.60

自引率

12.50%

发文量

147

审稿时长

6 months

期刊介绍： Ergonomics, also known as human factors, is the scientific discipline that seeks to understand and improve human interactions with products, equipment, environments and systems. Drawing upon human biology, psychology, engineering and design, Ergonomics aims to develop and apply knowledge and techniques to optimise system performance, whilst protecting the health, safety and well-being of individuals involved. The attention of ergonomics extends across work, leisure and other aspects of our daily lives. The journal Ergonomics is an international refereed publication, with a 60 year tradition of disseminating high quality research. Original submissions, both theoretical and applied, are invited from across the subject, including physical, cognitive, organisational and environmental ergonomics. Papers reporting the findings of research from cognate disciplines are also welcome, where these contribute to understanding equipment, tasks, jobs, systems and environments and the corresponding needs, abilities and limitations of people. All published research articles in this journal have undergone rigorous peer review, based on initial editor screening and anonymous refereeing by independent expert referees.