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The Measurement and Processing of EEG Signals to Evaluate Fatigue

机译:脑电信号评估疲劳的测量和处理

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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:疲劳和困倦对人脑的能力和正确进行能力的影响不大。人的疲劳和嗜睡是大脑效率低下和无效的主要原因。这种现象引起了学者们极大的心理社会学关注。监测EEG信号可以检测到极端疲劳状况并在诸如长途驾驶和单调锻炼等重要情况下发出警告。本文的目的是描述基于脑电图的疲劳信号测量并报告其可信度。方法:在警报和疲劳条件下所有主要EEG信号的变化被用于开发算法,以检测17位受试者在实验室条件下不同程度的疲劳。结果:经证明,MATLAB软件能够在17位接受测试的受试者中准确地识别出83%的疲劳。检测到受试者处于疲劳的不同阶段的时间百分比与警报阶段略有不同。讨论和辩论:据我们所知,这是所描述的第一个测量软件,该软件已显示出可根据不同频段的EEG信号变化检测疲劳。似乎需要更多的现场研究来评估疲劳软件,以产生一个强大而可靠的疲劳测量系统。

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