Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
333544 | Psychiatry Research | 2012 | 7 Pages |
Abstract
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.
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Authors
Cheol Seung Yoo, Dong Chung Jung, Yong Min Ahn, Yong Sik Kim, Su-Gyeong Kim, Hyeri Yoon, Young Jin Lim, Sang Hoon Yi,