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The Measurement and Processing of EEG Signals to Evaluate Fatigue

机译:EEG信号的测量和处理评估疲劳

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Fatigues and drowsiness infiuentially affect human minds ability and capability to proceed correctly. Human fatigue and drowsiness are a major cause of brain's inefficiency and ineffectiveness. This phenomenon is of great Psycho-sociological concerns among scholars. Monitoring EEG signals provides the possibility of detecting the extreme fatigue conditions and warning of it in vital circumstances such as long way driving and monotonous exercises. The aim of this paper is to describe an EEG-based fatigue signal measurements and to report its trustworthiness. Methodology: Changes in all major EEG signals during alert and fatigue conditions were used to develop the algorithm for detecting different levels of fatigue in laboratory conditions on 17 subjects. Results: The MATLAB software was shown to be able of identifying fatigue with 83% accurately in 17 subjects undergone the tests. The percentage of time the subjects were detected to be in different stages of fatigue was moderately different than the alert phase. Discussion and debates: To our knowledge, this is the first measurement software described that has shown to detect fatigue based on EEG signal changes in different frequency bands. It seems that more field research is required to evaluate the fatigue software in order to produce a robust and reliable fatigue measurement system.
机译:疲劳和嗜睡对人类思想能力和能力进行正确影响。人的疲劳和嗜睡是大脑低效率和无效的主要原因。这种现象是学者之间的巨大心理学关注。监控EEG信号提供了在重要的情况下检测它的极端疲劳条件和警告,例如长路驾驶和单调练习。本文的目的是描述基于EEG的疲劳信号测量,并报告其可靠性。方法论:警报和疲劳条件期间所有主要EEG信号的变化用于开发用于在17个受试者对实验室条件下检测不同水平的疲劳程度的算法。结果:MATLAB软件被证明能够在17个受试者中精确地识别83%的疲劳。检测到受试者被检测到不同疲劳阶段的时间百分比与警报相中异性不同。讨论和辩论:据我们所知,这是第一个描述的测量软件,其已经显示出基于不同频带中的EEG信号的变化来检测疲劳。似乎需要更多的现场研究来评估疲劳软件,以产生稳健且可靠的疲劳测量系统。

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