Automatic detection of seizure termination during electroconvulsive therapy using sample entropy of the electroencephalogram

作者：Yoo Cheol Seung; Jung Dong Chung; Ahn Yong Min; Kim Yong Sik; Kim Su Gyeong; Yoon Hyeri; Lim Young Jin; Yi Sang Hoon^*

来源：Psychiatry Research, 2012, 195(1-2): 76-82.

DOI：10.1016/j.psychres.2011.06.020

• electroconvulsive therapy
• seizure duration
• sample entropy
• complexity

Determining the exact duration of seizure activity is an important factor for predicting the efficacy of electroconvulsive therapy (ECT). In most cases, seizure duration is estimated manually by observing the electroencephalogram (EEG) waveform. In this article, we propose a method based on sample entropy (SampEn) that automatically detects the termination time of an ECT-induced seizure. SampEn decreases during seizure activity and has its smallest value at the boundary of seizure termination. SampEn reflects not only different states of regularity and complexity in the EEG but also changes in EEG amplitude before and after seizure activity. Using SampEn, we can more precisely determine seizure termination time and total seizure duration.

• 出版日期2012-1-30