1. Prediction of the effect of electrical defibrillation by using spectral feature parameters.
- Author
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Yoshikawa Y, Ogino Y, Okai T, Oya H, Hoshi Y, and Nakano K
- Subjects
- Humans, Support Vector Machine, Signal Processing, Computer-Assisted, Wavelet Analysis, Algorithms, Electrocardiography methods, Electric Countershock methods, Ventricular Fibrillation therapy, Ventricular Fibrillation physiopathology
- Abstract
This paper proposes a system for predicting the effect of electrical defibrillation using spectral feature parameters. The proposed method consists of two-stage prediction. The first stage involves predicting whether electrical defibrillation is "Successful" or "Ineffective." As the next stage, if the proposed prediction system determines "Ineffective," the proposed system discriminates between "VF recurrence" or "Failure" for electrical defibrillation. To develop the prediction system, feature parameters for the target electrocardiograms (ECGs) were first extracted by using the wavelet transform and spectral analysis. Next, effective feature parameters for prediction are selected through an analysis of variance. Moreover, in the preprocessing phase, the Synthetic Minority Oversampling Technique method and standardization are introduced. Finally, support vector machines with some kernel functions and the regularization method are utilized to predict the three states, i.e., "Successful," "Failure," and "VF recurrence," for electrical defibrillation in two phases. In this paper, we present our analysis method for ECGs and evaluate the effectiveness of the proposed prediction system., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Hidetoshi Oya reports a relationship with Japan Society for the Promotion of Science that includes: funding grants., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)
- Published
- 2024
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