Multiscale Sign Series Entropy Analysis Based On Sleep Electroencephalogram And The Young And Middle-aged Electroencephalogram

Electroencephalogram(EEG) records the brain activity of potential changes, it is the responses of electric signal of brain cell physiology activity in the cerebral cortex. Multiscale sign series entropy(MSSE) presented in this paper to analyze EEG signals under different physiological states,for clinical EEG analysis of pathology and physiology hope to have some reference value. In this paper, we analyze sleep EEG and the young and middle-aged EEG with MSSE, then implements the algorithm system.The content of the paper made as follows:(1) MSSE presented in this paper, I apply it to the analysis of pathological and physiological state of the sleep EEG. The results show that MSSE analysis algorithm can effectively distinguish between wakefulness and sleep two states, and it still can be able to analyze and detect different states in the case of affected by noise. By studying the results of this analysis, it shows that the algorithm can be used as an auxiliary method of clinical analysis and diagnosis of the sleep EEG.(2) In this paper, I analyze the young and middle-aged EEG with MSSE to analyze the EEG signals of different ages. Through analysis, this algorithm can effectively distinguish two different ages of young EEG and middle-aged EEG, and it also can detect the EEG signals of different ages with the influence of noise. Through the analysis, it shows that the analysis algorithm can assist clinical EEG analysis and diagnosis.(3) Implements algorithm MSSE system with C# programming, to analyze about sleep EEG and young and middle-aged EEG, in the case of different scales and in different modes, to analyze two groups of physiological EEG, and displays the results. By verifying shows that this system can effectively analysis EEG of different physiological state, it can play a supporting role in actual clinical assessment of brain function.