Analysis of alpha rhythm epileptic Electroencephalogram based on Inner composition alignment

Abstract

The EEG signal is an important tool for the diagnosis and prediction of epilepsy due to EEG containing a large number of physiological and pathological information. Based on alpha rhythm multi-channel EEG (electroencephalogram), this paper applied inner composition alignment (IOTA) algorithm to construct brain functional network and visualize the network topology. It is to apply the algorithm to calculate and analyze IOTA coefficient, the node average degree and clustering coefficient of epileptic brain network for studying if epileptic brain network is significantly different from those of normal. The results show that IOTA coefficient of epileptic brain network obviously differs from the normal by calculating T testing with SPSS software, which proved that the effectiveness of the algorithm to distinguish IOTA coefficient of epileptic brain network.