基于自适应Lempel-Ziv复杂度的情感脑电信号特征分析

ANALYSING EMOTIONAL EEG SIGNALS FEATURE BASED ON ADAPTIVE LEMPEL-ZIV COMPLEXITY

脑电信号是研究人类情感的主要手段之一。将Lempel-Ziv复杂度算法应用在脑电情感分类方面,并对其进行相应改进。针对脑电信号变化微弱的情况,在二值化过程对原有二值化方法进行改进,采用自适应方法调整信号分段区域,提取脑电情感数据特征,刻画了相邻点之间的相互关系和细节信息。探究不同情感状态下、不同电极复杂度的变化规律,采用SVM进行特征分类,验证了所提取特征的质量和有效性。

EEG signal is one of the primary means in studying human emotions.We apply the Lempel-Ziv complexity algorithm toemotional EEG classification,and make corresponding improvement on it.We improve the original binarisation method in binarisation processaiming at the situation of faint EEG signal variation,in it we use adaptive method to adjust signals’segmentation region,and extract EEGemotional data feature,which depicts the interrelationship between the adjacent points and the detailed information.We also explore thevariation rule in different emotional states and different electrode complexities,and classify the feature with SVM,as well as verify the qualityand effectiveness of the feature extracted.