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Software complex for the recognition of diagnostically significant ECG changes

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Abstract

A software complex for the automation of functional electrocardiographic (ECG) studies is presented. The algorithms of ECG signal processing and recognition of diagnostically significant ECG changes are considered. Methods of 3D visualization are proposed to increase the informativeness of electrocardiographic data and improve diagnostic accuracy.

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References

  1. A. P. Nemirko, “Processing and Automated Analysis of Electrocardiosignals,” Izv. SPbGETU LETI, Ser. Biotekh. Sist. Med. Ekolog., No. 1, 34 (2002).

  2. A. P. Nemirko, A. N. Kalinichenko, Y. I. Goncharenko, et al., “Software Package for the Functional Investigations Using ECG,” Pattern Recognition and Image Analysis 13(2), 308 (2003).

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Authors and Affiliations

  1. St. Petersburg State Electrotechnical University “LETI”, ul. Professora Popova 5, St. Petersburg, 197376, Russia

    A. P. Nemirko, A. N. Kalinichenko, P. V. Murashov, N. N. Pogodin, D. V. Goncharov & S. E. Ivanova

  2. Mikard-Lana, Furazhnyi per. 3, St. Petersburg, 191014, Russia

    C. M. Matous & A. N. Sankin

Authors
  1. A. P. Nemirko
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  2. A. N. Kalinichenko
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  3. P. V. Murashov
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  4. N. N. Pogodin
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  5. D. V. Goncharov
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  6. S. E. Ivanova
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  7. C. M. Matous
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  8. A. N. Sankin
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Nemirko, A.P., Kalinichenko, A.N., Murashov, P.V. et al. Software complex for the recognition of diagnostically significant ECG changes. Pattern Recognit. Image Anal. 16, 9–11 (2006). https://doi.org/10.1134/S1054661806010032

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  • DOI: https://doi.org/10.1134/S1054661806010032

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