Computer Engineering and Applications ›› 2019, Vol. 55 ›› Issue (9): 107-111.DOI: 10.3778/j.issn.1002-8331.1801-0290

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Research on Audiovisual EEG Based on Recurrence Quantification Analysis

LI Shidan, ZHU Xiaojun   

  1. College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China
  • Online:2019-05-01 Published:2019-04-28

基于递归定量分析的视听脑电应用研究

李世丹,朱晓军   

  1. 太原理工大学 计算机科学与技术学院,太原 030024

Abstract: The research of auditovisual integration EEG signal has enriched the field of brain cognition. However, most of existing EEG analysis methods are based on linear analysis methods, and require high SNR for data. Being a non-linear analysis method, the recursive quantitative analysis method based on the order recursive plot of phase space reconstruction has a lower noise requirement on the measured signals. It provides a new analysis method for the integration of audiovisual and auditory studies. Through the experiment of design different audiovisual stimulation paradigms, and EEG data of subject are collected under different stimulation paradigms. The phase space reconstruction is used in the preprocessed data to obtain the ordered recursive plot. Taking the Recursive Rate(RR) and deterministic(DET) as analysis parameters of integration effect. The experimental results show that this method can effectively analyze the visual and auditory integration effects from the perspective of nonlinear and it has high accuracy.

Key words: audiovisual integration, Electroencephalogram(EEG), recurrence quantification analysis

摘要: 视听觉整合的脑电信号研究丰富了脑认知领域的内容,但是现有的脑电信号分析方法大部分是基于线性的分析方法,同时对数据的信噪比要求较高。而基于相空间重构的排序递归图的递归定量分析方法对被测信号的噪声要求较低,并且是基于非线性的分析方法,为视听觉整合的研究提供了新的分析方法。设计不同视听刺激范式的实验,采集被试在不同刺激范式下的脑电数据。对预处理后的数据进行相空间重构,得到排序递归图。以递归率和确定性作为整合效果的分析参数。实验结果表明,该方法可以有效地从非线性角度分析视听觉整合效果,具有较高的准确性。

关键词: 视听整合, 脑电信号, 递归定量分析