Rabbi Ahmed F, Ivanca Kevin, Putnam Ashley V, Musa Ahmed, Thaden Courtney B, Fazel-Rezai Reza
Biomedical Signal Processing Laboratory, Electrical Engineering Department, University of North Dakota, ND 58202-7165 USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:1879-82. doi: 10.1109/IEMBS.2009.5333877.
Electroencephalogram (EEG) signal, the signature of brain activity, can be used to quantify for human performance evaluation. There are ongoing efforts by scientists and researchers in this area. Different traditional and novel signal processing and analysis methods have been applied to evaluate performance, mental workload, and task engagement based on EEG signals. Linear change in the indices with the increase in task difficulty was reported. In addition, EEG index has been used as parameter for performance optimization. In this review article, we will discuss briefly the literature on human performance estimation based on some physiological parameters, EEG in particular. In this paper, the current state of the research field is presented and possible future research options are discussed.
脑电图（EEG）信号作为大脑活动的特征，可用于量化人类表现以进行评估。该领域的科学家和研究人员正在不断努力。不同的传统和新颖的信号处理与分析方法已被应用于基于EEG信号评估表现、心理负荷和任务参与度。有报告称随着任务难度增加，指标呈线性变化。此外，EEG指标已被用作性能优化的参数。在这篇综述文章中，我们将简要讨论基于一些生理参数，特别是EEG的人类表现估计的文献。本文介绍了该研究领域的当前状态，并讨论了未来可能的研究方向。
