%0 Journal Article
%T THE ROLES OF DIFFERENT COMPONENTS OF EEGS FOR SEIZURE PREDICTION-WAVELET ENERGY EVALUATION
小波能量评价EEG的不同成分对癫痫发作预报的价值
%A ZHU Jun-ling
%A UN Hong
%A SU Chang-jun
%A SHEN Qiang
%A JIANG Da-zong
%A
朱俊玲
%A 林宏
%A 宿长军
%A 沈强
%A 蒋大宗
%J 生物物理学报
%D 2003
%I
%X Epilepsy, a chronic disorder of the nervous system affecting 1% of the population, is characterized by the abnormal synchronized firing of a large number of neurons. Alerting a patient and/or his attending staff to an impending epileptic seizure has obvious clinical importance. A lot of attempts at epileptic prediction have been made, some based on sharp-transient detection and some tracked changes in background activity. Wavelet transform was applied to 8 channel scalp EEGs recording from 3 epileptic patients of partial seizures secondarily generalized seizures. The data were sampled a couple of minutes or tens of minutes prior to the seizure onset. For each record and channel, the data was decomposed at 7 scales. Spike/sharp and slow wave components of EEGs can be highlighted at different scales. Energy of the spike/sharp and slow wave components was calculated from detail signal at different scales, respectively. Result: The energy of slow waves increased among 8 channels ahead of seizure onset several minutes hi all the 3 patients, but the energy of spike/sharp components had no trends. Conclusion: Slow wave components of EEGs are well suited for seizure prediction in partial type secondarily generalized seizures. High-amplitude slow waves of EEGs may be an important factor for seizure transition.
%K Epilepsy
%K Seizure
%K Prediction
%K EEG
%K Wavelet transform
癫痫
%K 发作
%K 预报
%K EEG
%K 小波变换
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=90BA3D13E7F3BC869AC96FB3DA594E3FE34FBF7B8BC0E591&jid=E0C9D9BBED813D6674AC13E942EAC86D&aid=EFE2DDD8CDCFF1DD&yid=D43C4A19B2EE3C0A&vid=2A8D03AD8076A2E3&iid=CA4FD0336C81A37A&sid=B9704B40A4225A24&eid=46CB27789995047D&journal_id=1000-6737&journal_name=生物物理学报&referenced_num=3&reference_num=13