Analysis of electrocardiosignals for formation of the diagnostic features of post-traumatic myocardial dystrophy
| Autor: | Ye. S. Karplyuk, G. V. Mjasnikov, O. V. Chesnokova, S. V. Sofienko, I. A. Chaikovskiy, N. G. Ivanushkina, K. O. Ivanko |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Basis (linear algebra)
medicine.diagnostic_test business.industry Dystrophy HR ECG post-traumatic myocardial dystrophy wavelet analysis eigenvector basis principal component analysis Pattern recognition 02 engineering and technology 030204 cardiovascular system & hematology Covariance 03 medical and health sciences 0302 clinical medicine Wavelet decomposition Wavelet Statistics Principal component analysis 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing Artificial intelligence Electrical and Electronic Engineering business Electrocardiography Eigenvalues and eigenvectors Mathematics |
| Zdroj: | Radioelectronics and Communications Systems; Том 60, № 9 (2017); 405-412 |
| ISSN: | 0735-2727 1934-8061 |
| Popis: | The possibilities of high-resolution electrocardiography (HR ECG) application for diagnostics of post-traumatic myocardial dystrophy having multifactorial genesis is considered in this paper. Numerical processing and analysis of electrocardiograms that belong to patients from armed forces after explosive-driven injuries have been performed based on clinical studies. Complex method of cardiosignal analysis based on combination of wavelet analysis, eigenvector decomposition and principal component analysis is developed. This method revealed that low-amplitude deviations in ECG signal in case of post-traumatic myocardial dystrophy have low-frequency nature that is linked to slow electro-physiological processes. It is shown that these low-frequency, low-amplitude components appear at a high levels (8th and 9th) of decomposition in case of 9-level wavelet decomposition of averaged cardio cycles. Integral parameters for identification of post-traumatic myocardial dystrophy features are suggested and determined on the basis of principal component analysis. These parameters are squared sum of signal projections to eigenspaces Hk and mean eigenvalues of covariance matrices of electrocardiosignals ensembles λmean. |
| Databáze: | OpenAIRE |
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