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Principal Components Method for Heart Rate Variability Analysis

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Biomedical Engineering Aims and scope

Results of analysis of an informative set of heart rate variability (HRV) indicators are presented. The analysis is made using the principal components method. We identified components that are the most sensitive to functional changes in the body, such as evaluation of autonomic balance determined by ratio LF wt /HF wt (where HF wt is a wavelet transform of the HRV spectrum intensity for the frequency range from 0.4 to 0.15 Hz, and LF wt is that for the frequency range from 0.15 to 0.04 Hz) and dysfunctions of the functional F[LF wt /HF wt ], where N is the number of dysfunctions; A max is maximum value and A is intensity in the observation interval. The efficiency of the method was tested on a group of patients with stage II-III essential hypertension during treatment with the use of hypotensive therapy and the SIMPATOKOR -01 apparatus.

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References

  1. R. M. Baevskii et al., Vestnik Aritmologii, 65-87 (2002).

  2. V. J. Samar, A. Bopardikar, R. Rao, and K. Swartz, Brain and Language, 66, 7-60 (1999).

    Article  Google Scholar 

  3. V. S. Kublanov, and V. L. Gasilov, Biomed. Tekhnol. Radioelektron., No. 11, 12-20 (2001).

  4. H. Yang, S. T. Bukkapatnam, and R. Komanduri, Phys. Rev. E76: Statistical, Nonlinear, and Soft Matter Physics, 76, 026214 (2007).

    Article  Google Scholar 

  5. V. S. Kublanov, V. B. Kostousov, Ya. E. Kazakov, and A. A. Popov, Biomed. Radioelektron., No. 1-2, 13-25 (2008).

  6. Ya. A. Torivskii, S. D. Kurgalin, and A. A. Vakhtin, Biomed. Radioelektron., No. 12, 39-45 (2012).

  7. J. Rafiee, M. A. Rafiee, N. Prause, and M. P. Schoen, Expert Systems with Applications, 38, 6190-6201 (2011).

    Article  Google Scholar 

  8. D. N. Lawley, and A. E. Maxwell, Factor Analysis as a Statistical Method [Russian translation], Mir, Moscow (1967).

    Google Scholar 

  9. A. M. Dubrov, Processing of Statistical Data with Method of Principle Components [in Russian], Statistika, Moscow (1978).

    Google Scholar 

  10. V. N. Kainina, and V. I. Solov’ev, Introduction to Multidimetional Statistical Analysis [in Russian], Gosuniversitet Upravleniya, Moscow (2003).

    Google Scholar 

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Authors and Affiliations

  1. Ural Federal University, Ekaterinburg, Russia

    D. D. Egorova & V. S. Kublanov

  2. Medical Technologies Ltd., Ekaterinburg, Russia

    Ya. E. Kazakov

Authors
  1. D. D. Egorova
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  2. Ya. E. Kazakov
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  3. V. S. Kublanov
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Corresponding author

Correspondence to D. D. Egorova.

Additional information

Translated from Meditsinskaya Tekhnika, Vol. 48, No. 1, Jan.–Feb., 2014, pp. 33–37.

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Egorova, D.D., Kazakov, Y.E. & Kublanov, V.S. Principal Components Method for Heart Rate Variability Analysis. Biomed Eng 48, 37–41 (2014). https://doi.org/10.1007/s10527-014-9412-7

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  • DOI: https://doi.org/10.1007/s10527-014-9412-7

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