A Novel Method in Attention Measurement for Operators of Radar Devices Based on P300 Event-Related Potential Protocols Detection

Q3 Energy
S. A. Karimi, S. Mirzakuchaki
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引用次数: 0

Abstract

Various methods have been proposed to detect the attention and perception of an operator during tasks such as radar monitoring. Due to the high accuracy of electroencephalographic signals, it is utilized for systems based on brain signal. The eventrelated potential (ERP) technique has been widely used for testing theories of perception and attention. Brain-computer Interface (BCI) provides the communication link between the human’s brain and an external device. In this article, we propose a method to investigate the attention of operators of very sensitive monitoring devices, in particular, the operators of navy ships’ radars in detecting fighter aircrafts. Using a Visual Stimuli, which was shown to the subjects prior to the test, the protocol utilized in this paper yielded a very high accuracy (up to 87%), which makes it a robust method to use in such conditions. Linear LDA and non-linear SVM classifiers were utilized in processing the output signal. Although several P300 systems have been used to detect attention using pattern recognition techniques, the novelty of this study is that attention detection is used for the first time for a radar operator which resulted in acceptable accuracy.
基于P300事件相关潜在协议检测的雷达设备操作人员注意力测量新方法
在雷达监测等任务中,已经提出了各种方法来检测操作员的注意力和感知。由于脑电图信号具有较高的准确性,它被用于基于脑信号的系统。事件相关电位(eventrelated potential, ERP)技术被广泛应用于知觉理论和注意理论的检验。脑机接口(BCI)提供了人脑与外部设备之间的通信链接。在本文中,我们提出了一种方法来调查非常敏感的监测设备的操作员,特别是海军舰艇雷达操作员在探测战斗机时的注意力。使用在测试前向受试者展示的视觉刺激,本文中使用的协议产生了非常高的准确性(高达87%),这使其成为在这种条件下使用的稳健方法。利用线性LDA和非线性SVM分类器对输出信号进行处理。尽管一些P300系统已被用于使用模式识别技术检测注意力,但本研究的新颖之处在于,注意力检测首次用于雷达操作员,从而获得了可接受的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Iranian Journal of Electrical and Electronic Engineering
Iranian Journal of Electrical and Electronic Engineering Engineering-Electrical and Electronic Engineering
CiteScore
1.70
自引率
0.00%
发文量
13
审稿时长
12 weeks
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