Recurrence Quantification Analysis Of Epileptic EEG Based On Cross Recurrence Plot And Order Recurrence Plot

Epilepsy is a kind of brain dysfunction syndrome, the life of patients will be greatly affected by epilepsy. In recent years, epilepsy has become a high incidence of disease. Because there are many causes of epilepsy, the treatment of epilepsy is very difficult. Electroencephalogram is an important kind of bioelectricity contains many important physiological and pathological information. The nonlinear method was used to classify and analyze EEG signals of epileptic patients and healthy persons in this thesis.The thesis mainly focus on the following aspects:(1) Cross Recurrence Plot(CRP)can analyze the similarity of two nonlinear time sequences, it was applied to the analysis of different EEG leads in this thesis. The quantitative detection was also carried out base on RQA. Experiment proves that the coupling of different leads of epileptic EEG is stronger.(2) Order Recurrence Plot(ORP)was improved based on RP through symbolic dynamics. We used ORP to analyze one lead EEG. The results shows that the epileptic EEG have stronger deterministic rate. As a kind of nonlinear dynamic system, The Chaos Characteristics of brain will be affected by epilepsy.(3) We develop an APP based on RQA algorithm. After the EEG signal processing, we can view the ORP CRP and compute the RQA parameters through APP. The analysis system can be used to mobile brain function monitoring and diagnosis.