Application of the Discriminant Analysis for Diagnostics of the Arterial Hypertension - Analysis of Short-Term Heart Rate Variability Signals

Vladimir Kublanov, Anton Dolganov, Vasilii Borisov

2016

Abstract

The investigation of the diagnostic possibilities for the arterial hypertension is presented. The 41 features of the statistical, geometric, spectral and nonlinear methods during functional loads were considered for two groups: healthy volunteers and patients suffering from the arterial hypertension of the II-III degree. Application of the linear and quadratic discriminant analysis showed particular features that have high classification efficiency.

References

  1. Baevskiy, R. M., 2001. ?naliz variabelnosti serdechnogo ritma pri ispolzovanii razlichnykh ehlektrokardiograficheskikh sistem (metodicheskie rekomendatsii) [Analysis of heart rate variability using different electrocardiographic systems (guidelines)]. Vestnik aritmologii [Herald Arhythmology], (24), 65-87.
  2. Cinaz, B., Arnrich, B., La Marca, R., Tröster, G., 2013. Monitoring of mental workload levels during an everyday life office-work scenario. Personal and Ubiquitous Computing, 17 (2), 229-239.
  3. Ebrahimi, F., Setarehdan, S.-K., Ayala-Moyeda, J., Nazeran, H., 2013. Automatic sleep staging using empirical mode decomposition, discrete wavelet transform, time-domain, and nonlinear dynamics features of heart rate variability signals. Computer Methods and Programs in Biomedicine, 112 (1), 47-57.
  4. Egorova, D. D., Kazakov, Y. E., Kublanov, V. S., 2014. Principal Components Method for Heart Rate Variability Analysis. Biomedical Engineering, 48 (1), 37-41.
  5. Ihlen, E. A. F., 2012. Introduction to multifractal detrended fluctuation analysis in Matlab. Frontiers in Physiology, 3 JUN.
  6. Jain, A. K., Duin, R. P. W., Mao, J., 2000. Statistical pattern recognition: A review. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22 (1), 4-37.
  7. Krzanowski, W. J., 2000. Principles of multivariate analysis: a user's perspective. Rev edition. Oxford Oxfordshire. New York: Oxford University Press.
  8. Lewis, M. J., Short, A. L., Suckling, J., 2012. Multifractal characterisation of electrocardiographic RR and QT time-series before and after progressive exercise. Computer Methods and Programs in Biomedicine, 108 (1), 176-185.
  9. Lin, D. C., Sharif, A., 2012. Integrated central-autonomic multifractal complexity in the heart rate variability of healthy humans. Frontiers in Physiology, 2 FEB.
  10. Makowiec, D., Rynkiewicz, A., Wdowczyk-Szulc, J., Zarczynska-Buchowiecka, M., 2012. On reading multifractal spectra. multifractal age for healthy aging humans by analysis of cardiac interbeat time intervals. Acta Physica Polonica B, Proceedings Supplement, 5 (1), 159-170.
  11. Malik, M., 1996. Heart rate variability: Standards of measurement, physiological interpretation, and clinical use. Circulation, 93 (5), 1043-1065.
  12. Melillo, P., Bracale, M., Pecchia, L., 2011. Nonlinear Heart Rate Variability features for real-life stress detection. Case study: students under stress due to university examination. BioMedical Engineering OnLine, 10 (96), 1-13.
  13. Melillo, P., Pacifici, E., Orrico, A., Iadanza, E., and Pecchia, L., 2014. Heart rate variability for automatic assessment of congestive heart failure severity. IFMBE Proceedings, 41, 1342-1345.
  14. Sivanantham, A., Shenbaga Devi, S., 2014. Cardiac arrhythmia detection using linear and non-linear features of HRV signal. In: 2014 International Conference on Advanced Communication Control and Computing Technologies (ICACCCT). 795-799.
  15. Stanley, H. E., Amaral, L. A. N., Goldberger, A. L., Havlin, S., Ivanov, P. C., Peng, C.-K., 1999. Statistical physics and physiology: Monofractal and multifractal approaches. Physica A: Statistical Mechanics and its Applications, 270 (1-2), 309-324.
  16. Suslina, A., Varakin, Y. Y., 2015. Clinical guidelines for the early diagnosis, treatment and prevention of vascular diseases of the brain. [in Russian]. Moscow: MEDpress-inform.
  17. Wilkinson, J. B., Waring, S., 2005. Cockroft DR Arterial hypertension. Answers to your questions. London: Elsevier Syns.
Download


Paper Citation


in Harvard Style

Kublanov V., Dolganov A. and Borisov V. (2016). Application of the Discriminant Analysis for Diagnostics of the Arterial Hypertension - Analysis of Short-Term Heart Rate Variability Signals . In Proceedings of the 4th International Congress on Neurotechnology, Electronics and Informatics - Volume 1: NEUROTECHNIX, ISBN 978-989-758-204-2, pages 45-52. DOI: 10.5220/0006044000450052


in Bibtex Style

@conference{neurotechnix16,
author={Vladimir Kublanov and Anton Dolganov and Vasilii Borisov},
title={Application of the Discriminant Analysis for Diagnostics of the Arterial Hypertension - Analysis of Short-Term Heart Rate Variability Signals},
booktitle={Proceedings of the 4th International Congress on Neurotechnology, Electronics and Informatics - Volume 1: NEUROTECHNIX,},
year={2016},
pages={45-52},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006044000450052},
isbn={978-989-758-204-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Congress on Neurotechnology, Electronics and Informatics - Volume 1: NEUROTECHNIX,
TI - Application of the Discriminant Analysis for Diagnostics of the Arterial Hypertension - Analysis of Short-Term Heart Rate Variability Signals
SN - 978-989-758-204-2
AU - Kublanov V.
AU - Dolganov A.
AU - Borisov V.
PY - 2016
SP - 45
EP - 52
DO - 10.5220/0006044000450052