NONLINEAR DYNAMICS AND CHAOTIC INDEXES IN HEART-RATE-VARIABILITY OF NORMAL SUBJECTS AND HEART-TRANSPLANTED PATIENTS

Citation
S. Guzzetti et al., NONLINEAR DYNAMICS AND CHAOTIC INDEXES IN HEART-RATE-VARIABILITY OF NORMAL SUBJECTS AND HEART-TRANSPLANTED PATIENTS, Cardiovascular Research, 31(3), 1996, pp. 441-446
Citations number
27
Categorie Soggetti
Cardiac & Cardiovascular System
Journal title
ISSN journal
00086363
Volume
31
Issue
3
Year of publication
1996
Pages
441 - 446
Database
ISI
SICI code
0008-6363(1996)31:3<441:NDACII>2.0.ZU;2-U
Abstract
Objectives: Heart rate variability (HRV) is characterised by a variety of linear, non-linear, periodical and non-periodical oscillations. Th e aim of the present study was mainly to investigate the role played b y neural mechanisms in determining non-linear and non-periodical compo nents. Methods: Analysis was performed in 7 recently heart transplante d patients and in 7 controls of similar age whose HRV signal was colle cted during 24 h. Parameters that quantify non-linear dynamic behaviou r, in a time series, were calculated. We first assessed the specific n on-linear nature of the time series by a test on surrogate data after Fourier phase randomization. Furthermore, the D-2 correlation dimensio n, K-2 Kolmogorov entropy, and H self-similarity exponent of the signa l were estimated. From this last parameter, the dimension D = 1/H can be obtained. In order to assess whether the dynamics of the system are compatible with chaotic characteristics, the entire spectrum of Lyapu nov exponents was calculated. We used return maps to graphically repre sent the non-linear and non-periodical behaviours in patients and cont rols. Results: Surrogate data suggest that the HRV time courses have u nique non-linear characteristics. D-2, K-2 and 1/H parameters were sig nificantly lower in transplanted subjects than in controls, Positivity of the first Lyapunov exponent indicates divergence of trajectories i n state-space. Furthermore, the display of return maps on projections obtained after Singular Value Decomposition, especially in low-complex ity data (as in transplanted patients), shows a structure which is sug gestive of a strange attractor. These findings support the hypothesis that chaotic dynamics underlie HRV. Conclusion: These results indicate that non-linear dynamics are likely to be present in HRV control mech anisms, giving rise to complex and qualitatively different behaviours. System complexity decreases in transplanted patients and this may be related to loss of the neural modulation of heart rate.