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青霉素诱发癫痫性脑电图尖峰的自动分类

Automatic classification of penicillin-induced epileptic EEG spikes.

作者信息

Kortelainen Jukka, Silfverhuth Minna, Suominen Kalervo, Sonkajarvi Eila, Alahuhta Seppo, Jantti Ville, Seppanen Tapio

机构信息

Department of Electrical and Information Engineering, BOX 4500, FIN-90014 University of Oulu, Finland.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:6674-7. doi: 10.1109/IEMBS.2010.5627154.

Abstract

Penicillin-induced focal epilepsy is a well-known model in epilepsy research. In this model, epileptic activity is generated by delivering penicillin focally to the cortex. The drug induces interictal electroencephalographic (EEG) spikes which evolve in time and may later change to ictal discharges. This paper proposes a method for automatic classification of these interictal epileptic spikes using iterative K-means clustering. The method is shown to be able to detect different spike waveforms and describe their characteristic occurrence in time during penicillin-induced focal epilepsy. The study offers potential for future research by providing a method to objectively and quantitatively analyze the time sequence of interictal epileptic activity.

摘要

青霉素诱发的局灶性癫痫是癫痫研究中一种众所周知的模型。在该模型中,通过将青霉素局部注入皮层来产生癫痫活动。该药物诱发发作间期脑电图(EEG)尖峰,这些尖峰随时间演变,随后可能转变为发作期放电。本文提出了一种使用迭代K均值聚类对这些发作间期癫痫尖峰进行自动分类的方法。结果表明,该方法能够检测不同的尖峰波形,并描述它们在青霉素诱发的局灶性癫痫发作期间随时间出现的特征。该研究通过提供一种客观、定量分析发作间期癫痫活动时间序列的方法,为未来的研究提供了潜力。

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