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Design and Development of a Heart Rate Variability Analyzer

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Abstract

Heart rate variability (HRV), analysis gives an insight into the state of the autonomic nervous system which modulates the cardiac activity. Here a digital signal controller based handy device is developed which acquires the beat to beat time interval, processes it using techniques based on non-linear dynamics, fractal time series analysis, and information theory. The technique employed, that can give reliable results by assessing heart beat signals fetched for a duration of a few minutes, is a huge advantage over the already existing methodologies of assessing cardiac health, those being dependant on the tedious task of acquiring Electro Cardio Gram(ECG) signals, which in turn requires the subject to lie down at a stretch for a couple of hours. The sensor used, relies on the technique of Photoplethysmography, rendering the whole approach as noninvasive. The device designed, calculates parameters like, Largest Lyapunov Exponent, Fractal dimension, Correlation Dimension, Approximate Entropy and α-slope of Poincare plots, which based on the range in which they fall, the cardiac health condition of the subject can be assessed to even the extend of predicting upcoming disorders. The design of heart beat sensor, the technique used in the acquisition of heart beat data, the relevant algorithm developed for the analysis purpose, are presented here.

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References

  1. Paul Josph, K., Suri, J. S., and Rajendra Acahraya, U., Heart rate variability: a review. Med. Biol. Eng. Comput. 44:1031–1051, 2006.

    Article  Google Scholar 

  2. Lown, B., and Verrier, R. L., Neural activity and ventricular fibrillation. N. Engl. J. Med. 294:1165–1170, 1976.

    Article  Google Scholar 

  3. Corr, P. B., Yamada, K. A., and Witkowski, F. X., Mechanisms controlling cardiac autonomic function and their relation to arrhythmogenesis. In: Fozzard, H. A., Haber, E., Jennings, R. B., Katz, A. N., and Morgan, H. E. (Eds.), The Heart and Cardiovascular System. Raven, New York, pp. 1343–1403, 1986.

    Google Scholar 

  4. Schwartz, P. J., and Priori, S. G., Sympathetic nervous system and cardiac arrhythmias. In: Zipes, D. P., and Jalife, J. (Eds.), Cardiac Electrophysiology: From Cell to Bedside. WB Saunders, Philadelphia, pp. 330–343, 1990.

    Google Scholar 

  5. Levy, M. N., and Schwartz, P. J. (Eds.), Vagal Control of the Heart: Experimental Basis and Clinical Implications. Futura, Armonk, 1994.

    Google Scholar 

  6. Malliani, A., Pagani, M., Lombardi, F., and Cerutti, S., Cardiovascular neural regulation explored in the frequency domain. Circulation. 84:1482–1492, 1991.

    Google Scholar 

  7. Kamath, M. V., and Fallen, E. L., Power spectral analysis of heart rate variability: a noninvasive signature of cardiac autonomic function. Crit. Rev. Biomed. Eng. 21:245–311, 1993.

    Google Scholar 

  8. Appel, M. L., Berger, R. D., Saul, J. P., Smith, J. M., and Cohen, R. J., Beat to beat variability in cardiovascular variables: noise or music? J. Am. Coll. Cardiol. 14:1139–1148, 1989.

    Article  Google Scholar 

  9. Appel, M. L., Berger, R. D., Saul, J. P., Smith, J. M., and Cohen, R. J., Beat to beat variability in cardiovascular variables: noise or music? J. Am. Coll. Cardiol. 14:1139–1148, 1989.

    Article  Google Scholar 

  10. Allen, J., Photoplethysmography and its application in clinical physiological measurement. Physiol. Meas. 28(3):R1–R39, 2007.

    Article  Google Scholar 

  11. Henry, B., Lovell, N., and Camacho, F., Non linear dynamics time series analysis. Non linear biomedical signal processing Vol. 2- Dynamic analysis and modeling, Wiley-IEEE press, 2000.

  12. Takens, F., Detecting strange attractors in turbulence. In: Rand, D. A., and Young, L. S. (Eds.), Dynamical Systems and Turbulence. Springer, Berlin, 1981.

    Google Scholar 

  13. Sauer, T., Yorke, J., and Casdagli, M., Embedology. J. Stat. Phys. 65:579–616, 1994.

    Article  MathSciNet  Google Scholar 

  14. Wolf, A., Swift, J. B., Swinney, H. L., and Vastano, J. A., Determining Lyapunov exponents from a time series. Physica D. 16:285–317, 1985.

    Article  MathSciNet  MATH  Google Scholar 

  15. Liebert, W., and Schuster, H. G., Proper choice of the time delay for analysis of chaotic time series. Phys. Lett. A 142:107, 1989.

    Article  MathSciNet  Google Scholar 

  16. Grassberger, P., and Procaccia, I., Characterization of strange attractors. Phys. Rev. Lett. 50(5):346–349, 1983.

    Article  MathSciNet  Google Scholar 

  17. Pincus, S. M., Approximate entropy as a measure of system complexity. Proc. Natl. Acad. Sci. USA. 88:2297–2301, 1991.

    Article  MathSciNet  MATH  Google Scholar 

  18. Ki H, C., Scully, C. G., and Lu, S., Approximate entropy for all signals. IEEE engineering in medicine and biology magazine, November/December 2009, pp 18–23

  19. Khaled, A. S., Owis, M. I., and Mohamed, A. S. A., Employing time-domain methods and poincaré plot of heart rate variability signals to detect congestive heart failure. BIME Journal, 6(1), 2006.

  20. Piskorski, J., and Guzik, P., Filtering poincare plots. Comput. Methods Sci. Technol. 11(1):39–48, 2005.

    Google Scholar 

  21. Acharya, U. R., Kannathal, N., and Krishnan, S. M., Comprehensive analysis of cardiac health during heart rate signals. Physiol. Meas. J. 25:1130–1151, 2004.

    Google Scholar 

  22. Acharya, U. R., Kannathal, N., Seng, O. W., Ping, L. Y., and Chua, T., Heart rate analysis in normal subjects of various age groups. Biomed Online J. USA 3(24), 2004

  23. Peng, C. K., Buldyrev, S. V., Havlin, S., Simons, M., Stanley, H. E., and Goldberger, A. L., Mosaic organization of DNA nucleotides. Phys. Rev. E. 49:1685–1689, 1994.

    Article  Google Scholar 

  24. Yeh, R.-G., Shieh, J. S., Han, Y. Y., Yu-Jungwang, and Tseng, S. C., Detrended fluctuation analyses of short-term heart rate variability in surgical intensive care units. Biomed. Eng. Appl. Basis Commun. 18:67–72, 2006.

    Article  Google Scholar 

  25. Rojo-Alvarez, J. L., Sanchez-Sanchez, A., Barquero-Perez, O., Goya-Esteban, R., Everss, E., Mora-Jimenez, I., and Garcia-Alberola, A., Analysis of physiological meaning of detrended fluctuation analysis in heart rate variability using a lumped parameter model. Comput. Cardiol. 34:25–28, 2007.

    Google Scholar 

  26. Smith, S. W., Ph.D. Chapter 2: Statistics: Probability and Noise. The Scientist and Engineer’s Guide to Digital Signal Processing. Available online at http://www.dspguide.com/ch2.htm (last checked on 25-Aug-2010.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Institute of Technology Calicut, Calicut, India

    Aparna Mohan, Frana James, Sajeer Fazil & Paul K. Joseph

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  1. Aparna Mohan
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  2. Frana James
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  4. Paul K. Joseph
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Correspondence to Paul K. Joseph.

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Mohan, A., James, F., Fazil, S. et al. Design and Development of a Heart Rate Variability Analyzer. J Med Syst 36, 1365–1371 (2012). https://doi.org/10.1007/s10916-010-9597-6

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  • DOI: https://doi.org/10.1007/s10916-010-9597-6

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