Phase Synchronization in Sleep Electroencephalogram

The EEG signals are highly subjective and the information about the various states may appear at random in the time scale. Therefore, EEG signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. The EEG signals are so complicated that traditional methods for nonlinear dynamic analysis, such as correlation dimension, Lyapunov exponent, detrended fluctuation analysis, cannot fully characterize their nature. In this paper, the sleep EEG data analysis is carried out using phase synchronization method. At first, the algorithm is introduced. Then, a discussion is made on its merits and dismerits. For 8 healthy volunteers without any medication, analysis of EEG using phase synchronization is performed. Results show that the phase synchronization index of EEG signals during sleep process can correctly affect sleep deepness, and accord with the results of sleep stage by expert.