消极情绪状态自动识别的脑电信号频谱特征

2019 IEEE XXVIII International Scientific Conference Electronics (ET) Pub Date : 2019-09-01 DOI:10.1109/ET.2019.8878557

F. Feradov, T. Ganchev

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引用次数: 3

摘要

在本文中，我们研究了频谱脑电图特征的性质，以检测消极情绪状态。特别是，基于多通道脑电信号的时频分析，所提出的特征代表了20-35 Hz频率范围内能量分布的动态。实验评估基于DEAP数据库的数据。我们报告了基于J48和基于smo的分类器的结果，平均分类准确率分别为94.3%和96.8%。

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Spectral Features of EEG Signals for the Automated Recognition of Negative Emotional States

In the presented paper we investigate the properties of spectral EEG features for the detection of negative emotional states. In particular, the proposed features represent the dynamics of energy distribution in the frequency range of 20–35 Hz, based on a time-frequency analysis of multichannel EEG signal. The experimental evaluation is based on data from the DEAP database. We report results with J48- and SMO-based classifiers, in terms of average classification accuracy, 94.3% and 96.8%, respectively.

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2019 IEEE XXVIII International Scientific Conference Electronics (ET)

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