Abstract
ECG(electrocardiogram) signal is an important basis to diagnose heart diseases, but its a weak low-frequency non-stationary signal, and possessing noise setting strong characters, neither time-domain nor frequency-domain based methods are suitable for analyzing this signal. In this article we adopt time-frequency analysis approaches which could reflect signal both in time and frequency domains. Totally, we adopts two time-frequency approaches: Pseudo-Wigner–Ville Distribution (PWVD) and Wigner High-Order Spectra(WHOS), we successfully extract characters from two kinds abnormal ECG signals, which improves our methods are effective.
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Song, L., Yu, F. (2010). The Time-Frequency Analysis of Abnormal ECG Signals. In: Li, K., Jia, L., Sun, X., Fei, M., Irwin, G.W. (eds) Life System Modeling and Intelligent Computing. ICSEE LSMS 2010 2010. Lecture Notes in Computer Science(), vol 6330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15615-1_8
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DOI: https://doi.org/10.1007/978-3-642-15615-1_8
Publisher Name: Springer, Berlin, Heidelberg
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