关键词: 脑电信号, 复杂网络, 模糊系统, 机器学习

Abstract: Identifying seizures from EEG signals is a crucial tool in clinical diagnosis of epilepsy. However, the accuracy of manually labeling EEG signals is barely satisfactory. In this paper, a method based on functional brain network and TSK fuzzy system is proposed to identify seizures from EEG signals. Functional brain networks of epileptics are constructed by analyzing the synchronization between multi-channel EEG signals. Complex network theory is further applied to extract topological features of brain networks. Taken the network parameters as independent inputs, a fuzzy system based TSK model is established and further trained through supervised learning to identify seizures. Experimental results demonstrate the effectiveness of the proposed scheme. The accuracy, sensitivity and specificity of seizure states identification are 98.36%, 99.48%, and 97.24%, respectively. The novel method, combining complex network theory with machine learning algorithm, provides a potential tool for identifying epilepsy state from EEG signals, which has important values in clinical application.

Key words: EEG, complex network, fuzzy system, machine learning