脑电波信号处理及其在教育中的应用研究

发布时间：2018-02-28 21:03

本文关键词： 脑电波信号处理线性预测器眨眼伪迹教育应用　出处：《华中师范大学》2016年硕士论文　论文类型：学位论文

【摘要】：近年来,随着生物信息技术的高速发展,脑电波及信号处理已成为脑科学和神经信息学的重要研究方向。脑电波作为一种微弱的生物电信号,经过脑电设备的采集,如何从携带噪声的脑电信号中分离和滤除掉伪迹,并得到纯净、无噪声污染的脑电信号,是专家学者研究的重点。经过伪迹去除后的脑电波,其提供的有用信息,在临床医学、生理学、心理学及教育方面的应用也越来越广泛。本文讨论了脑电波及信号处理,在处理眨眼伪迹方面提出了一种彻底、真实还原脑电纯净信号的算法。并研发了一套以学生注意力提升为导向的测试系统,探讨脑电波在教育方面的应用前景。在人类思考的时候,其磁场效应会发生作用,从而会形成一种称为脑电波的生物电流。本文首先介绍了脑电波的产生机理及研究发展历程,并对脑电波信号处理的国内外研究成果作了简要的归纳和阐述,接着分析了脑电波在教育方面的应用案例,得出使用脑电波进行注意力训练是一种新型有效的注意力训练方式。引出了脑电波信号处理及教育应用的课题及研究意义。其次,根据作者对脑电信号处理方面的研究,对比分析了多电极脑电设备与单电极脑电设备采集数据的区别,对脑电信号处理中需要用到的数学分析模型进行深入研究,并详细阐述脑电信号时域分析、频域分析和时频分析。在此基础上,重点研究单电极脑电信号的眨眼伪迹去除算法。通过分析现有的眨眼伪迹去除算法,针对已有去除单电极脑电信号眨眼伪迹的ICA与小波模型相结合算法的不足,提出了一种基于自适应线性预测器的AR模型算法,通过对比分析和实验,其结果证明该算法在去除眨眼伪迹和还原真实干净的脑电信号方面,切实可行,且具有一定的优越性。最后,本文基于该算法处理后的真实脑电信号,研发了一套应用于教育教学研究的注意力测试系统,从需求分析、系统设计与主要模块实现等方面做了较为详尽的阐述,使用该系统,进行注意力的分组测试,取得了一系列的成果。例如采用多样化的教学方式,通过多样化的媒体资源展示,能提高学生注意力,取得更好的教学效果。
[Abstract]:In recent years, with the rapid development of biological information technology, brain wave and signal processing have become an important research direction of brain science and neuroinformatics. How to separate and filter artifacts from noise-carrying EEG signals and get pure, noise-free EEG signals is the focus of research by experts and scholars. The useful information provided by EEG waves after removing artifacts is in clinical medicine. Physiology, psychology, and education are also becoming more and more widely used. This paper discusses brain wave and signal processing, and proposes a new method for processing blink artifacts. An algorithm for true reduction of pure EEG signals. A set of student-oriented testing systems were developed to explore the application of brain waves in education. When humans think, the magnetic field effects work. In this paper, the mechanism of brain wave generation and its research and development are introduced, and the research results of brain wave signal processing at home and abroad are briefly summarized and expounded. Then it analyzes the application of brain wave in education, and draws a conclusion that using brain wave to train attention is a new and effective method of attention training, and leads to the subject and research significance of brain wave signal processing and educational application. According to the author's research on EEG signal processing, the differences between multi-electrode EEG equipment and single-electrode EEG equipment are compared and analyzed, and the mathematical analysis model used in EEG signal processing is deeply studied. The time domain analysis, frequency domain analysis and time frequency analysis of EEG signal are described in detail. On this basis, the blink artifact removal algorithm of single electrode EEG signal is studied. An AR model algorithm based on adaptive linear predictor is proposed to solve the problem of combining ICA with wavelet model to remove blink artifact of single electrode EEG signal. Through contrast analysis and experiment, an AR model algorithm based on adaptive linear predictor is proposed. The results show that the algorithm is feasible in removing blink artifacts and reducing real and clean EEG signals. Finally, based on the real EEG signals processed by this algorithm, A set of attention test system is developed, which is applied to educational teaching research. It is described in detail from the aspects of requirement analysis, system design and main module realization. The system is used to carry out attention grouping test. A series of achievements have been achieved, such as adopting diversified teaching methods and displaying various media resources, which can improve students' attention and achieve better teaching results.
【学位授予单位】：华中师范大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TN911.7;TP311.52

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