Home // eTELEMED 2020, The Twelfth International Conference on eHealth, Telemedicine, and Social Medicine // View article
Authors:
Chun-Hsiang Huang
Po-Hsun Huang
Tzu-Chien Hsiao
Keywords: Electrocardiography; Empirical Mode Decomposition; Ensemble Empirical Mode Decomposition; Reconstruction error
Abstract:
Electrocardiography (ECG) is an important test in the diagnosis of heart disease. The analysis of T waves in the ECG is an essential clinical tool, however, it is often difficult to extract the T waves from the ECG. Empirical Mode Decomposition (EMD) can decompose nonlinear and nonstationary signals, but this method suffers from the problem of mode mixing. Ensemble Empirical Mode Decomposition (EEMD) can solve the mode mixing problem but generates a new problem, namely, that of the reconstruction error. Moreover, noise may remain in the decomposed signals and pollute the waveforms. Therefore, we propose a new method based on EEMD to solve these problems and to decompose the T wave from ECG. The results show that the T waves’ waveforms can be successfully decomposed in the fourth Intrinsic Mode Functions (IMFs) in all 3 cases studied, namely, no noise, power line noise, and Gaussian white noise.
Pages: 109 to 114
Copyright: Copyright (c) IARIA, 2020
Publication date: March 22, 2020
Published in: conference
ISSN: 2308-4359
ISBN: 978-1-61208-763-4
Location: Valencia, Spain
Dates: from November 21, 2020 to November 25, 2020