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Emotion Recognition Based on Framework of BADEBA-SVM

机译：基于Badeba-SVM框架的情感识别

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摘要

Brain-computer interface (BCI) provides a new communication channel between human brain and computer. In order to eliminate uncorrelated channels to improve BCI performance and enhance user convenience with fewer channels, this paper proposes a new framework using binary adaptive differential evolution bat algorithm (BADEBA). The framework uses the important ideas of differential evolution algorithm and bat algorithm to select electroencephalograph (EEG) channels and intelligently optimizes the parameters of support vector machine (SVM). It combines wavelet packet transform (WPT) and common space pattern (CSP) to achieve the goal of using fewer channels to obtain the best classification accuracy. The proposed framework is evaluated with a common data set (DEAP). The results show that, compared with genetic algorithm (GA), binary particle swarm optimization (BPSO) and bat algorithm, the proposed BADEBA in this framework only uses eight channels to improve the classification accuracy by 13.63% in the valence dimension and seven channels to improve the classification accuracy by 15.22% in the arousal dimension. In addition, the spatial distribution of the best channels selected by this method is consistent with the existing knowledge of brain structure and neurophysiology, which shows the accuracy and validity of this method.
机译：脑电脑界面（BCI）提供人脑和计算机之间的新通信通道。为了消除不相关的通道，以提高BCI性能并通过较少的频道增强用户便利性，提出了一种使用二元自适应差分演进BAT算法（Badeba）的新框架。该框架使用差分演进算法和BAT算法的重要思路选择脑电图（EEG）通道，并智能地优化支持向量机（SVM）的参数。它结合了小波包变换（WPT）和公共空间模式（CSP）来实现使用较少信道获得最佳分类精度的目标。通过常见的数据集（DEAP）评估所提出的框架。结果表明，与遗传算法（GA），二进制粒子群优化（BPSO）和BAT算法相比，该框架中的提议Badeba仅使用八个通道，以在价维和七个频道中提高13.63％的分类精度。在唤醒维度中提高分类精度15.22％。此外，该方法选择的最佳通道的空间分布与脑结构和神经生理学的现有知识一致，这表明了该方法的准确性和有效性。

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  • 来源
    《Mathematical Problems in Engineering》 |2019年第15期|38.1-38.9|共9页
  • 作者

    Wang Zhongmin; Zhang Zhaoping; Wang Wenlang;

  • 作者单位

    Xian Univ Posts & Telecommun Sch Comp Sci & Technol Xian 710121 Shaanxi Peoples R China|Xian Univ Posts & Telecommun Shaanxi Key Lab Network Data Anal & Intelligent P Xian 710121 Shaanxi Peoples R China;

    Xian Univ Posts & Telecommun Shaanxi Key Lab Network Data Anal & Intelligent P Xian 710121 Shaanxi Peoples R China;

    Xian Univ Posts & Telecommun Sch Comp Sci & Technol Xian 710121 Shaanxi Peoples R China|Xian Univ Posts & Telecommun Shaanxi Key Lab Network Data Anal & Intelligent P Xian 710121 Shaanxi Peoples R China;

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