School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200444, China.
School of Civil Engineering, Tsinghua University, Beijing, 100084, China.
Sci Rep. 2023 Sep 29;13(1):16356. doi: 10.1038/s41598-023-43477-0.
Complex assembly tasks with multiple manual operations and steps often require rapid judgment and action under time pressure and cause most human-related errors. The task switching and action transitions are major sources of these errors. This study intends to implement an electroencephalography (EEG) approach to quantitatively evaluate the mental workload during task switching and transition. The time-frequency and spectrum analysis were utilized to compute and reflect the task demand between the intervals of individual tasks. This study developed an experiment to validate the proposed assessment approach and benchmark the results with the National Aeronautics and Space Administration task load index (NASA-TLX) subjective evaluation scale analysis. The results show that the average value of the power spectral densities (PSDs) of the gamma band signal of the AF4 channel and the beta band signal of Channel F3 show distinctive signal patterns among task stages and intervals. During the interval between the idling stage and the part selection stage, the peak of the PSD envelope increased from 18 to 27 Hz, suggesting advanced cognition increases the mental workload of the interval between different tasks. Therefore, the task switching period cannot be regarded as rest and need to be optimized with better task organization.
复杂的装配任务涉及多个手动操作和步骤，通常需要在时间压力下做出快速判断和行动，这容易导致大多数人为错误。任务切换和操作转换是这些错误的主要来源。本研究旨在实施一种脑电图（EEG）方法，以定量评估任务切换和转换过程中的心理工作量。本研究采用时频和频谱分析来计算和反映个体任务间隔之间的任务需求。本研究设计了一个实验来验证所提出的评估方法，并将结果与美国国家航空航天局任务负荷指数（NASA-TLX）主观评估量表分析进行基准比较。结果表明，AF4 通道伽马波段信号和 F3 通道贝塔波段信号的平均功率谱密度（PSD）值在任务阶段和间隔之间呈现出明显的信号模式。在空闲阶段和零件选择阶段之间的间隔期间，PSD 包络的峰值从 18 赫兹增加到 27 赫兹，这表明高级认知增加了不同任务之间间隔的心理工作量。因此，任务切换期间不能被视为休息时间，需要通过更好的任务组织进行优化。
