Intraclass correlations of seizure duration by wavelet transform, sample entropy, and visual determination in electroconvulsive therapy. Issue 1 (31st December 2019)

• Record Type: Journal Article
• Authors: Azuma, Hideki; Ogawa, Haruka; Suzuki, Erina; Akechi, Tatsuo
• Is Part Of: Neuropsychopharmacology reports. Volume 40:Issue 1(2020)
• Page Start: 102
• Page End: 106
• Publication Date: 2019-12-31
• Subjects: ECT -- EEG -- sample entropy -- seizure duration -- wavelet transform; Neuropsychopharmacology -- Periodicals; 615.78
• DOI: 10.1002/npr2.12095
• Languages: English
• ISSNs: 2574-173X

Abstract

Abstract: Although electroconvulsive therapy seizure duration has been shown to have limited relevance to efficacy, seizure duration remains important for clinically valid stimulus efficiency. There has been no report on seizure duration using sample entropy with Thymatron (Somatics, Inc), which is widely used in Japan. Furthermore, wavelet transform analysis is also suitable for a seizure because of the wide range of dominant frequencies. Therefore, in this study with Thymatron, the intraclass correlations of seizure duration determined by sample entropy, wavelet transform, and visual determination were investigated to determine whether these methods were applicable for clinical use. Wavelet transform, sample entropy, and the human rater had high intraclass correlations for seizure duration. The present results indicate that wavelet transform and sample entropy can be useful in the clinical electroconvulsive therapy setting, and they may also be suitable for clinical research into the mechanisms of the generalized tonic‐clonic seizures related to the efficacy of electroconvulsive therapy. Abstract : The intraclass correlations of electroconvulsive therapy‐induced seizure duration determined by sample entropy, wavelet transform, and visual determination were investigated to determine whether these methods were applicable for clinical use. sample entropy, wavelet transform, and the human rater had high intraclass correlations for the seizure durations. The present results indicate that sample entropy and wavelet transform can be useful in the clinical electroconvulsive therapy setting.