工作量
认知负荷
任务(项目管理)
计算机科学
认知
感知
信息处理
认知心理学
听力学
心理学
应用心理学
工程类
医学
精神科
神经科学
操作系统
系统工程
作者
Haizhe Jin,Lin Zhu,Mingming Li,Vincent G. Duffy
出处
期刊:Ergonomics
[Informa]
日期:2023-06-20
卷期号:67 (3): 377-397
被引量:2
标识
DOI:10.1080/00140139.2023.2223785
摘要
This study explores the effects of different perceptual and cognitive information processing stages on mental workload by assessing multimodal indicators of mental workload such as the NASA-TLX, task performance, ERPs and eye movements. Repeated measures ANOVA of the data showed that among ERP indicators, P1, N1 and N2 amplitudes were sensitive to perceptual load (P-load), P3 amplitude was sensitive to P-load only in the prefrontal region during high cognitive load (C-load) states, and P3 amplitude in the occipital and parietal regions was sensitive to C-load. Among the eye movement indicators, blink frequency was sensitive to P-load in all C-load states, but to C-load in only low P-load states; pupil diameter and blink duration were sensitive to both P-load and C-load. Based on the above indicators, the k-nearest neighbours (KNN) algorithm was used to propose a classification method for the four different mental workload states with an accuracy of 97.89%.Practitioner summary: Based on the results of this study, it is possible to implement the monitoring of mental workload states and optimise brain task allocation in operations involving high mental workload, such as human-computer interaction.
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