Fractal dimension of heart rate time series: an effective measure of autonomic function

Yeragani, V.; Srinivasan, Krishnamachari; Vempati, S.; Pohl, Robert; Balon, Richard

doi:10.1152/jappl.1993.75.6.2429

Cited by 97 publications

(61 citation statements)

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“…We observed a marked reduction of sample entropy with the change of position from supine to standing, which is in agreement with observations by Yeragani et al (25). This fact indicates the simplification of heart rate control in standing with predominance of LF rhythm after reduction of vagal influences on the heart following parasympathetic withdrawal and sympathetic activation (25).…”

Section: Autonomic Nervous System Hrv and Exercisesupporting

confidence: 92%

“…This fact indicates the simplification of heart rate control in standing with predominance of LF rhythm after reduction of vagal influences on the heart following parasympathetic withdrawal and sympathetic activation (25). During post-exercise recovery sample entropy was slightly decreased compared to supine rest before exercise and regained supine rest values after 30 min.…”

Section: Autonomic Nervous System Hrv and Exercisementioning

confidence: 89%

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Heart rate recovery after exercise: relations to heart rate variability and complexity

Javorka

Žila

Balhárek

et al. 2002

Braz J Med Biol Res

243

192

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Physical exercise is associated with parasympathetic withdrawal and increased sympathetic activity resulting in heart rate increase. The rate of post-exercise cardiodeceleration is used as an index of cardiac vagal reactivation. Analysis of heart rate variability (HRV) and complexity can provide useful information about autonomic control of the cardiovascular system. The aim of the present study was to ascertain the association between heart rate decrease after exercise and HRV parameters. Heart rate was monitored in 17 healthy male subjects (mean age: 20 years) during the pre-exercise phase (25 min supine, 5 min standing), during exercise (8 min of the step test with an ascending frequency corresponding to 70% of individual maximal power output) and during the recovery phase (30 min supine). HRV analysis in the time and frequency domains and evaluation of a newly developed complexity measure -sample entropy -were performed on selected segments of heart rate time series. During recovery, heart rate decreased gradually but did not attain pre-exercise values within 30 min after exercise. On the other hand, HRV gradually increased, but did not regain rest values during the study period. Heart rate complexity was slightly reduced after exercise and attained rest values after 30-min recovery. The rate of cardiodeceleration did not correlate with pre-exercise HRV parameters, but positively correlated with HRV measures and sample entropy obtained from the early phases of recovery. In conclusion, the cardiodeceleration rate is independent of HRV measures during the rest period but it is related to early postexercise recovery HRV measures, confirming a parasympathetic contribution to this phase.

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Section: Autonomic Nervous System Hrv and Exercisesupporting

confidence: 92%

Section: Autonomic Nervous System Hrv and Exercisementioning

confidence: 89%

Heart rate recovery after exercise: relations to heart rate variability and complexity

Javorka

Žila

Balhárek

et al. 2002

Braz J Med Biol Res

243

192

View full text Add to dashboard Cite

show abstract

“…In our previous reports, we found that approximate entropy (APEN) and fractal dimension (FD), using the method of Katz (1988), correlated highly significantly with each other and also with the HF power on spectral analysis (Yeragani et al, 1993b(Yeragani et al, , 1997. Unlike these measures, MED, LLE and NL measures had no substantial correlation with any of the time-domain measures (Radhakrishna et al, 2000).…”

Section: Discussionmentioning

confidence: 85%

“…We have previously used a similar technique to perform band analysis of the signal using FD and APEN (Yeragani et al, 1993b). We attempted to compare how each of these bands contributes toward the non-linearity and chaos of the UF time series.…”

Section: Filtering Of the Time Seriesmentioning

confidence: 99%

“…Recent literature has shown the utility of nonlinear measures of heart rate (HR) variability to study cardiac autonomic function in health and disease (Goldberger and West, 1987;Katz, 1988;Glenny et al, 1991;Pincus et al, 1991;Yeragani et al, 1993bYeragani et al, , 1997Guzzetti et al, 1996;Lombardi et al, 1996;Voss et al, 1996;Ho et al, 1997;Braun et al, 1998;Storella et al, 1998;Kagiyama et al, 1999;Silipo et al, 1999;Yeragani et al, 2000). Analysis of time series using methods of non-linear dynamics can be performed by the estimation of Lyapunov exponents (LE) and degree of non-linearity (NL).…”

Section: Introductionmentioning

confidence: 99%

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Heart rate time series: decreased chaos after intravenous lactate and increased non-linearity after isoproterenol in normal subjects

Yeragani

Rao

Jayaraman

et al. 2002

Psychiatry Research

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In this study, we reanalyzed our previous heart rate time series data on the effects of intravenous sodium lactate (ns9) and intravenous isoproterenol (ns11) using non-linear techniques. Our prior findings of significantly higher baseline non-linear scores (NL: S ) and significantly lower largest Lyapunov exponents in supine posture in netGS patients with panic disorder compared to control subjects prompted this study. We obtained the largest Lyapunov exponent (LLE), and a measure of non-linearity (NL: S ) of heart rate time series. LLE quantifies predictability netGS and NL quantifies the deviation from linear processes. There was a significant increase in NL score, (S ) after netGS isoproterenol infusions and a significant decrease in LLE (an increase in predictability indicating decreased chaos), after intravenous lactate in supine posture in normal control subjects. Increased NL scores in supine posture after intravenous isoproterenol may be due to a relative increase in cardiac sympathetic activity or a decrease in vagal activity at least in certain circumstances, and an overall decrease in LLE may indicate an impaired cardiac autonomic flexibility after intravenous sodium lactate, as LLE is diminished by autonomic blockade by atropine. Band analysis of LLE (LFyHF) (LF: 0.04 -0.15 Hz and HF: 0.15 -0.5 Hz) showed an increase of these ratios during either condition with a higher sympathovagal interaction after the drug administration. These findings may throw new light on the association of anxiety and significant cardiovascular events. ᮊ

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Nonlinear measures of heart period variability: Decreased measures of symbolic dynamics in patients with panic disorder

et al. 2000

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Time series of heart period are not linear and recent studies illustrated the importance of using nonlinear methods to quantify the complexity of these time series. We compared different techniques to quantify the nonlinear complexity of these time series in patients with panic disorder and normal controls and correlated these measures with spectral powers in different bands of interest. Twenty‐four hour ECG was recorded in 23 normal controls and 29 patients with panic disorder by using Holter records. Time series of heart period were analyzed by using approximate entropies, slopes of 1/f scaling, two algorithms to calculate fractal dimension, and word sequences using symbolic dynamics. Measures using symbolic dynamics, especially word count (WC‐100), showed highly significant differences between the two groups similar to some of the frequency domain (spectral) measures, while the other techniques were relatively ineffective to distinguish between the two groups. Different nonlinear techniques may relate to different aspects of nonlinear complexity of the time series. These nonlinear techniques were also not uniform in showing the differences between awake and sleep periods. Some correlate with the measures of respiratory sinus arrhythmia and some measures obtained from symbolic dynamics may reflect not only the nonlinear complexity of the time series but also the total variability in the 24 hr HP time series, especially power in the ultra‐low frequency band (<0.0033 Hz). However, word count (WC‐100) had only weak correlations with other measures and discriminated best between the two groups and showed that this nonlinear measure was of additional value to the linear measures in classifying the two groups. Depression and Anxiety 12:67–77, 2000. © 2000 Wiley‐Liss, Inc.

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Fractal dimension of heart rate time series: an effective measure of autonomic function

Cited by 97 publications

References 0 publications

Heart rate recovery after exercise: relations to heart rate variability and complexity

Heart rate recovery after exercise: relations to heart rate variability and complexity

Heart rate time series: decreased chaos after intravenous lactate and increased non-linearity after isoproterenol in normal subjects

Nonlinear measures of heart period variability: Decreased measures of symbolic dynamics in patients with panic disorder

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