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Using Supervised Fuzzy Clustering and CWT for Ventricular Late Potentials (VLP) Detection in High-Resolution ECG Signal

  • Conference paper
11th Mediterranean Conference on Medical and Biomedical Engineering and Computing 2007

Part of the book series: IFMBE Proceedings ((IFMBE,volume 16))

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Abstract

Ventricular Late Potentials (VLPs) are lowamplitude, high-frequency signals that appear at the end of the QRS complex of a High-Resolution ECG (HRECG) records. VLPs are clinically useful for identifying post-MI (Myocardial Infarction) patients prone to Ventricular Tachycardia (VT) and Sudden Cardiac Death (SCD). In this paper, the Continuous Wavelet Transform (CWT) and a supervised fuzzy clustering algorithm are used together to detect VLPs. The terminal part of the QRS complex in the Vector Magnitude (VM) waveform is processed with the CWT to extract a feature vector. Resulting time-scale representation is subdivided into several sub bands, and the sum of the squared decomposition coefficients is computed in each region. Finally, a supervised Fuzzy clustering method, trained by an appropriate set of these feature vectors, is applied to this data in order to identify VLP.

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Jafari, A., Morradi, M. (2007). Using Supervised Fuzzy Clustering and CWT for Ventricular Late Potentials (VLP) Detection in High-Resolution ECG Signal. In: Jarm, T., Kramar, P., Zupanic, A. (eds) 11th Mediterranean Conference on Medical and Biomedical Engineering and Computing 2007. IFMBE Proceedings, vol 16. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73044-6_26

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  • DOI: https://doi.org/10.1007/978-3-540-73044-6_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73043-9

  • Online ISBN: 978-3-540-73044-6

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