Improved ECG-Derived Respiration Using Empirical Wavelet Transform and Kernel Principal Component Analysis
Autor: | Fenlan Li, Alex Noel Joseph Raj, Vijayarajan Rajangam, Zhemin Zhuang, Shuxin Zhuang, Wenbin Rao |
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Rok vydání: | 2021 |
Předmět: |
Article Subject
General Computer Science Correlation coefficient Computer science General Mathematics Computer applications to medicine. Medical informatics R858-859.7 Wavelet Analysis Neurosciences. Biological psychiatry. Neuropsychiatry Kernel principal component analysis Square (algebra) Reduction (complexity) Electrocardiography Coherence (signal processing) Principal Component Analysis business.industry Respiration General Neuroscience Wavelet transform Signal Processing Computer-Assisted Pattern recognition General Medicine Nonlinear system Radial basis function kernel Artificial intelligence business Algorithms RC321-571 Research Article |
Zdroj: | Computational Intelligence and Neuroscience Computational Intelligence and Neuroscience, Vol 2021 (2021) |
ISSN: | 1687-5273 1687-5265 |
Popis: | Many methods have been developed to derive respiration signals from electrocardiograms (ECGs). However, traditional methods have two main issues: (1) focusing on certain specific morphological characteristics and (2) not considering the nonlinear relationship between ECGs and respiration. In this paper, an improved ECG-derived respiration (EDR) based on empirical wavelet transform (EWT) and kernel principal component analysis (KPCA) is proposed. To tackle the first problem, EWT is introduced to decompose the ECG signal to extract the low-frequency part. To tackle the second issue, KPCA and preimaging are introduced to capture the nonlinear relationship between ECGs and respiration. The parameter selection of the radial basis function kernel in KPCA is also improved, ensuring accuracy and a reduction in computational cost. The correlation coefficient and amplitude square coherence coefficient are used as metrics to carry out quantitative and qualitative comparisons with three traditional EDR algorithms. The results show that the proposed method performs better than the traditional EDR algorithms in obtaining single-lead-EDR signals. |
Databáze: | OpenAIRE |
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