基于局部子集特征选择和改进的Dempster-Shafer理论的情绪识别新方法。

IF 4.7 2区 心理学 Q1 BEHAVIORAL SCIENCES
Morteza Zangeneh Soroush, Keivan Maghooli, Seyed Kamaledin Setarehdan, Ali Motie Nasrabadi
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引用次数: 29

摘要

背景:情绪识别是脑机交互中一个日益重要的研究领域。导读:随着科技的进步,自动情绪识别系统不再遥不可及。尽管如此,检测情绪的神经关联仍然是一个实质性的瓶颈。解决这一问题将是一个具有重大意义的文献突破。方法:本研究旨在通过合适的电极来确定不同情绪与大脑区域之间的相关性。首先采用独立分量分析算法去除伪影,提取独立分量。然后根据获得的组件的阈值平均活动值选择信息通道。然后,从所有情感类别之间共同的通道中提取有效特征。使用局部子集特征选择方法对特征进行约简,然后使用改进的Dempster-Shafer证据理论将特征输入到新的分类模型中。结果:将该方法应用于DEAP数据集,并与前人的研究结果进行了比较,结果表明该方法通过脑电图识别情绪的能力显著,准确率约为91%。最后,对所得结果进行了讨论,并介绍了新的研究方向。结论:目前的研究解决了寻找人类情绪和激活的大脑区域之间的神经关联的长期挑战。同时,我们成功地解决了情感分类中最具挑战性的问题之一的不确定性问题。该方法可用于未来的其他实际应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A novel approach to emotion recognition using local subset feature selection and modified Dempster-Shafer theory.

A novel approach to emotion recognition using local subset feature selection and modified Dempster-Shafer theory.

A novel approach to emotion recognition using local subset feature selection and modified Dempster-Shafer theory.

A novel approach to emotion recognition using local subset feature selection and modified Dempster-Shafer theory.

Background: Emotion recognition is an increasingly important field of research in brain computer interactions.

Introduction: With the advance of technology, automatic emotion recognition systems no longer seem far-fetched. Be that as it may, detecting neural correlates of emotion has remained a substantial bottleneck. Settling this issue will be a breakthrough of significance in the literature.

Methods: The current study aims to identify the correlations between different emotions and brain regions with the help of suitable electrodes. Initially, independent component analysis algorithm is employed to remove artifacts and extract the independent components. The informative channels are then selected based on the thresholded average activity value for obtained components. Afterwards, effective features are extracted from selected channels common between all emotion classes. Features are reduced using the local subset feature selection method and then fed to a new classification model using modified Dempster-Shafer theory of evidence.

Results: The presented method is employed to DEAP dataset and the results are compared to those of previous studies, which highlights the significant ability of this method to recognize emotions through electroencephalography, by the accuracy of about 91%. Finally, the obtained results are discussed and new aspects are introduced.

Conclusions: The present study addresses the long-standing challenge of finding neural correlates between human emotions and the activated brain regions. Also, we managed to solve uncertainty problem in emotion classification which is one of the most challenging issues in this field. The proposed method could be employed in other practical applications in future.

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来源期刊
Behavioral and Brain Functions
Behavioral and Brain Functions 医学-行为科学
CiteScore
5.90
自引率
0.00%
发文量
11
审稿时长
6-12 weeks
期刊介绍: A well-established journal in the field of behavioral and cognitive neuroscience, Behavioral and Brain Functions welcomes manuscripts which provide insight into the neurobiological mechanisms underlying behavior and brain function, or dysfunction. The journal gives priority to manuscripts that combine both neurobiology and behavior in a non-clinical manner.
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