title: Automatic detection of seizure termination during electroconvulsive therapy using sample entropy of the electroencephalogram.
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.
authors.affiliation: Institute of Human Behavioral medicine, Seoul National University College of Medicine, 28 Yongon-Dong, Chongno-Gu, Seoul 110-744, Republic of Korea.
authors.forename: Cheol Seung
authors.initials: CS
authors.lastname: Yoo
authors.forename: Dong Chung
authors.initials: DC
authors.lastname: Jung
authors.forename: Yong Min
authors.initials: YM
authors.lastname: Ahn
authors.forename: Yong Sik
authors.initials: YS
authors.lastname: Kim
authors.forename: Su-Gyeong
authors.initials: SG
authors.lastname: Kim
authors.forename: Hyeri
authors.initials: H
authors.lastname: Yoon
authors.forename: Young Jin
authors.initials: YJ
authors.lastname: Lim
authors.forename: Sang Hoon
authors.initials: SH
authors.lastname: Yi
mesh_terms: D004565:Electroconvulsive Therapy / Q000379:methods; D004569:Electroencephalography / Q000379:methods*; D001330:Electronic Data Processing / Q000379:methods*; D019277:Entropy; D005583:Fourier Analysis; D006801:Humans; D017063:Outcome Assessment, Health Care / Q000379:methods*; D012640:Seizures / Q000503:physiopathology* / Q000628:therapy; D013997:Time Factors