title: [Symbolic dynamics analysis of epileptic EEG signals of the rat].
abstract: Epilepsy is a common chronic neurological disease, which is caused by excessive brain neuron discharge. The epileptic seizure has the characteristic of abruptness and reiteration. Prediction of seizures has great significance for patients to take timely and effective clinical measures. The symbolic dynamics method was introduced to analyze absence epilepsy EEG. The key parameters affecting the symbolic statistical quantities were discussed. The symbolic entropy and time irreversebility were calculated in different epilepsy stages. It was found that the symbolic entropy and the time irreversebility were rather big in interictal stage. The two parameters declined significantly during the transformation process from interictal stage to ictal stage and maintained lower value during ictal stage. The results showed that the symbolic dynamics method could reflect the changes of epilepsy EEG. The symbolic entropy and time irreversebility are sensitive features indicating different stages of seizures and have potential important clinical applications.
authors.affiliation: Department of Biomedical Engineering, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China. zhaoyong@ysu.edu.cn
authors.forename: Yong
authors.initials: Y
authors.lastname: Zhao
authors.forename: Wenxue
authors.initials: W
authors.lastname: Hong
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000503:physiopathology*; D004569:Electroencephalography; D004827:Epilepsy / Q000503:physiopathology*; D008297:Male; D051381:Rats; D011919:Rats, Inbred Strains; D012815:Signal Processing, Computer-Assisted