A Method to Detect Ventricular Fibrillation in Electrocardiograms
Journal
2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO)
Date Issued
2021-09-27
Author(s)
Temelkov, G.
DOI
10.23919/mipro52101.2021.9596913
Abstract
The objective of this research is to create an algorithm for automatic detection of ventricular fibrillation in electrocardiogram records customized for wearable single-channel sensors. Our approach is based on observing and examining sequences of ventricular fibrillation in their frequency-domain. The research, design, and validation process, along with comprehensive annotations, is carried out on Physionet reference databases. We use a sliding window approach and apply the Fast Fourier Transform to convert the data from the time domain to the frequency domain. Our approach is based on the determination of frequency peaks, calculation of energy around the peak, and its ratio to the overall spectra. The evaluation of detection performance classification results by applying the digital signal processing algorithms with machine learning methods classify ventricular arrhythmia episodes with F1 score of 0.77 and accuracy of 0.92.