Analysis Of EEG Based On Mutual Mode Entropy

The brian is the most complex organ in human body.Thousands of researches have been madeabout brain in modern medicine,and one of the most important methods iselectroencephalogram(EEG).In this paper,we presented an algorithm named Mutual ModeEntropy(MME) to quantify the degree of coupling between two simultaneous acquisition of EEGtime series.We proved our work well-behaved through analysis and hypothesis testing of threedifferent clinical data.Firstly,We take the middle-age and the teenager’s EEG as the sample toanalyze the difference,and results show that the MME of the middle-age has a higher value than theteenager’s,which indicates the algorithm has the ability to distinguish these two kinds of data.Infact,the higher MME value accord with the rule that human beings reach their intelligence peak inthe thirties.Secondly,we extract αrhythm from EEG of the middle-age and the teenager and applythe MME algorithm to the analsis of αrhythm.The conclusion is clear that the middle-age still hasa higher MME vaule than the teenager.Finally,the research of epileptic analysis show that theepileptic data has a larger MME value.In conclusion,the MME algorithm is effective and can be aparameter measuring brain state and assists future clinical evaluation of brain function. In order toachieve our research algorithms for clinical use, help doctors diagnose epilepsy, we achieve theabove algorithm on android systems.