Non-linear and chaos characteristics of heart sound time series

Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine

Volumn 222, Issue 3, 2008, Pages 265-272

  Li, B B ^a   Yuan, Z F ^a  

^a SICHUAN UNIVERSITY   (China)

Author keywords

C C method; Chaos; Fractal dimensions; Heart sound time series; Largest Lyapunov exponents

Indexed keywords

ABNORMAL MOVEMENT; BASED-ON CHAOS; C METHOD; C-C METHOD; CHAOS; CHAOS CHARACTERISTICS; CHAOTIC CHARACTERISTICS; CHAOTIC TIME SERIES; DYNAMIC MOVEMENTS; EMBEDDING DIMENSIONS; HEART SOUND SIGNAL; HEART SOUND TIME SERIES; HEART SOUNDS; LARGEST LYAPUNOV EXPONENT; LARGEST LYAPUNOV EXPONENTS; NON-LINEAR; NON-LINEAR DYNAMIC SYSTEMS; PHASE SPACES; PHYSICAL PHENOMENA; SCIENCE AND ENGINEERING;

CHAOTIC SYSTEMS; DIFFERENTIAL EQUATIONS; FRACTAL DIMENSION; LINEAR CONTROL SYSTEMS; LYAPUNOV METHODS; NONLINEAR SYSTEMS; PHASE SPACE METHODS; TIME SERIES; TIME SERIES ANALYSIS; CARDIOLOGY; CHAOS THEORY; FRACTALS; HEART; LINEAR SYSTEMS; LYAPUNOV FUNCTIONS; TIME DELAY;

CHAOS THEORY; TIME SERIES ANALYSIS;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; FRACTAL ANALYSIS; HEART RATE; HEART SOUND; HUMAN; METHODOLOGY; NONLINEAR SYSTEM; PHYSIOLOGY; SIGNAL PROCESSING; STANDARD; STATISTICS; TIME;

ALGORITHMS; FRACTALS; HEART RATE; HEART SOUNDS; HUMANS; MODELS, CARDIOVASCULAR; NONLINEAR DYNAMICS; PATTERN RECOGNITION, AUTOMATED; SIGNAL PROCESSING, COMPUTER-ASSISTED; STOCHASTIC PROCESSES; TIME FACTORS; WEIGHTS AND MEASURES;

EID: 47649101104     PISSN: 09544119     EISSN: None     Source Type: Journal    
DOI: 10.1243/09544119JEIM331     Document Type: Article

References (31)

1. Mayer-Kress, G. and Layne, S. P. Dimensional of the human electroencephalogram. Ann. N.Y. Acad. Sci., 1987, 504, 62-87.
2. Skinner, J. E., Carpeggiani, C., Landisman, C. E., and Fulton, K. W. Correlation dimension of heart beat intervals is reduced in conscious pigs by myocardial and hernia. Circulation Res., 1991, 68, 966-976.
3. Rogers, T. D., Yang, Z. C., and Yip, L. W. Complete chaos in a simple epidemiological model. J. Math. Biology, 1986, 23, 263-268.
4. May, R. M. Biological populations with nonover-lapping generations: stable points, stable cycles, and chaos. Science, 1974, 186, 645-647.
5. Wagner, C. D. and Persson, P. B. Nonlinear chaotic dynamics of arterial blood pressure and renal blood flow. Am. J. Physiology, 1985, 268, 621-627.
6. Gartinkel, A., Spano, M. L., Ditto, W. L., and Weiss, J. N. Controlling cardiac chaos. Science, 1992, 257, 1230-1235.
7. Stiff, S. J., Jerger, K., Duong, D. H., Chang, T., Spano, M. L., and Ditto, W. L. Controlling chaos in the brain. Nature, 1994, 370, 615-620.
8. Yamamoto, Y. and Hughson, R. L. Extracting fractal components from time series. Physica D, 1993, 68, 250-264.
9. Peng, C.-K., Havlin, S., Stanley, H. E., and Gold-berger, A. L. Quantification of scaling exponents and crossover phenomena in nonstationary heart beat time series. Chaos, 1995, 5, 82-87.
10. Pincus, S. Approximate entropy (ApEn) as complexity measure. C haos, 1995, 5, 110-117.
11. Ryan, S. M., Goldberger, A. L., Pincus, S. M., Mietus, J., and Lipsitz, L. A. Gender- and age-related differences in heart rate dynamics: are women more complex than men? J. Am. Coll. Cardiology, 1994, 24, 1700-1707.
12. Iyengar, N., Peng, C.-K., Morin, R., Goldberger, A. L., and Lipsitz, L. A. Age-related alterations in the fractal scaling of cardiac interbeat interval dynamics. Am. J. Physiology, 1996, 271, 1078-1084.
13. Pikkujamsa, S. M., Makikallio, T. H., Sourander, L. B., Raiha, I. J., Puukka, P., Skytta, J., Peng, C. K., Goldberger, A. L., and Huikuri, H. V. Cardiac interbeat interval dynamics from childhood to senescence. Circulation, 1999, 100, 393-399.
14. Tulppo, M. P., Makikallio, T. H., Seppanen, T., Shoemaker, K., Tutungi, E., Hughson, R. L., and Huikuri, H. V. Effects of pharmacological adrener-gic and vagal modulation on fractal heart rate dynamics. Clin. Physiology, 2001, 21, 515-523.
15. Srinivasan, K., Ashok, M. V., Vaz, M., and Yeragani, V. K. Effects of imipramine on linear and nonlinear measures of heart rate variability in children. Pediat. Cardiology, 2004, 25, 20-25.
16. Hegerman, I., Berglund, M., Lorin, M., Nowak, J., and Sylven, C. Chaos-related deterministic regulation of heart rate variability in time and frequency domains: effects of autonomic blockade and exercise. Cardiovascular Res., 1996, 31, 410-418.
17. Kagiyama, S., Tsukashima, A., Abe, I., Fujishima, S., Ohmori, S., Onaka, U., Ohya, Y., Fujii, K., Tsuchihashi, T., and Fujishima, M. Chaos and spectral analyses of heart rate variability during head-up tilting in essential hypertension. J. Autonomic Nerv. System, 1999, 76, 153-158.
18. Radhakrishna, R. K. A., Dutt, D. N., and Yeragani, V. K. Nonlinear measures of heart rate time series: influence of posture and controlled breathing. Autonomic Neurosci., 2000, 83, 148-158.
19. Kantz, H. and Schreiber, T. Nonlinear time series analysis, 1997 (Cambridge University Press, Cambridge).
20. Kiml, H. S., Eykholt, A. R., and Salas, J. D. Nonlinear dynamics, delay times, and embedding windows. Physica D, 1998, 127, 48-60.
21. Abraham, C., Biau, G., and Cadre, B. On Lyapunov exponent and sensitivity. J. Math. Analysis Applic., 2004, 290(2), 395-404.
22. Takens, F. Detecting strange attractors inturbu-lence. In Dynamical systems and turbulence, Lecture Notes in Mathematics, vol. 898, 1981, pp. 366-381 (Springer-Verlag, Berlin).
23. Stark, J., Broomhead, D. S., Davies, M. E., and Huke, J. Takens embedding theorems for forced and stochastic systems. Nonlinear Analysis: Theory, Meth. Applic., 1997, 30, 5303-5314.
24. Dang, J.-W. and Huang, J.-G. Study of the parameters used in calculating correlative dimension based on GP algorithm. Res. Computer Applic., 2004, 1, 46-50.
25. Yoganathan, A. P. Use of fast Fourier transform for frequency analysis of the first heart sound in normal man. Med. Biol. Engng, 1976, 14, 69-72.
26. Stein, P. H. Frequency spectra of the first heart sound of the aortic component and the second heart sound in patients with degenerated porcine bioprosthetic valves. Am. J. Cardiology, 1984, 53, 557-562.
27. Wu, X. and Huang, T. Computation of Lyapunov exponents in general relativity. Phys. Lett. A, 2003, 313, 77-81.
28. Wolf, A., Swift, J. B., Swinney, H. L., and Vastano, J. A. Determining Lyapunov exponents from a time series. Physica D, 1985, 16, 285-287.
29. Lu, J., Yang, G., Oh, H. , and Luo, A. C. J. Computing Lyapunov exponents of continuous dynamical systems method of Lyapunov vectors. Chaos, Solitons Fractals, 2005, 23, 1879-1892.
30. Eckmann, J. P., Kamphorst, O. S., Ruelle, D., and Ciliberto, S. Lyapunov exponents from time series. Phys. Rev., 1986, A34, 4971-4979.
31. Vuksanović, V. and Gal, V. Nonlinear and chaos characteristics of heart period time series: healthy aging and postural change. Autonomic Neurosci., 2005, 121, 94-100.