Operation Everest II: an indication of deterministic chaos in human heart rate variability at simulated extreme altitude

Recurrence Quantitative Analysis of Wavelet-Based Surrogate Data for Nonlinearity Testing in Heart Rate Variability

Exploring the presence of nonlinearity through surrogate data testing provides insights into the nature of physical and biological systems like those obtained from heart rate variability (HRV). Short-term HRV time series are of great clinical interest to study autonomic impairments manifested in chronic diseases such as the end stage renal disease (ESRD) and the response of patients to treatment with hemodialysis (HD). In contrast to Iterative Amplitude Adjusted Fourier Transform (IAAFT), the Pinned Wavelet Iterative Amplitude Adjusted Fourier Transform (PWIAAFT) surrogates preserve nonstationary behavior in time series, a common characteristic of HRV. We aimed to test synthetic data and HRV time series for the existence of nonlinearity. Recurrence Quantitative Analysis (RQA) indices were used as discriminative statistics in IAAFT and PWIAAFT surrogates of linear stationary and nonstationary processes. HRV time series of healthy subjects and 29 ESRD patients before and after HD were tested in this setting during an active standing test. Contrary to PWIAAFT, linear nonstationary time series may be erroneously regarded as nonlinear according to the IAAFT surrogates. Here, a lower proportion of HRV time series was classified as nonlinear with PWIAAFT, compared to IAAFT, confirming that the nonstationarity condition influences the testing of nonlinear behavior in HRV. A contribution of nonlinearity was found in the HRV data of healthy individuals. A lower proportion of nonlinear time series was also found in ESRD patients, but statistical significance was not found. Although this proportion tends to be lower in ESRD patients, as much as 60% of time series proved to be nonlinear in healthy subjects. Given the important contribution of nonlinearity in HRV data, a nonlinear point of view is required to achieve a broader understanding of cardiovascular physiology.

Heart rate variability changes at 2400 m altitude predicts acute mountain sickness on further ascent at 3000-4300 m altitudes

OBJECTIVE

If the body fails to acclimatize at high altitude, acute mountain sickness (AMS) may result. For the early detection of AMS, changes in cardiac autonomic function measured by heart rate variability (HRV) may be more sensitive than clinical symptoms alone. The purpose of this study was to ascertain if the changes in HRV during ascent are related to AMS.

METHODS

We followed Lake Louise Score (LLS), arterial oxygen saturation at rest (R-SpO(2)) and exercise (Ex-SpO(2)) and HRV parameters daily in 36 different healthy climbers ascending from 2400 m to 6300 m altitudes during five different expeditions.

RESULTS

After an ascent to 2400 m, root mean square successive differences, high-frequency power (HF(2 min)) of HRV were 17-51% and Ex-SpO(2) was 3% lower in those climbers who suffered from AMS at 3000 to 4300 m than in those only developing AMS later (≥5000 m) or not at all (all p < 0.01). At the altitude of 2400 m RMSSD(2 min) ≤ 30 ms and Ex-SpO(2) ≤ 91% both had 92% sensitivity for AMS if ascent continued without extra acclimatization days.

CONCLUSIONS

Changes in supine HRV parameters at 2400 m were related to AMS at 3000-4300 m Thus, analyses of HRV could offer potential markers for identifying the climbers at risk for AMS.

Operation Everest II

In October 1985, 25 years ago, 8 subjects and 27 investigators met at the United States Army Research Institute for Environmental Medicine (USARIEM) altitude chambers in Natick, Massachusetts, to study human responses to a simulated 40-day ascent of Mt. Everest, termed Operation Everest II (OE II). Led by Charlie Houston, John Sutton, and Allen Cymerman, these investigators conducted a large number of investigations across several organ systems as the subjects were gradually decompressed over 40 days to the Everest summit equivalent. There the subjects reached a V(O)(2)max of 15.3 mL/kg/min (28% of initial sea-level values) at 100 W and arterial P(O(2)) and P(CO(2)) of approximately 28 and approximately 10 mm Hg, respectively. Cardiac function resisted hypoxia, but the lungs could not: ventilation-perfusion inequality and O(2) diffusion limitation reduced arterial oxygenation considerably. Pulmonary vascular resistance was increased, was not reversible after short-term hyperoxia, but was reduced during exercise. Skeletal muscle atrophy occurred, but muscle structure and function were otherwise remarkably unaffected. Neurological deficits (cognition and memory) persisted after return to sea level, more so in those with high hypoxic ventilatory responsiveness, with motor function essentially spared. Nine percent body weight loss (despite an unrestricted diet) was mainly (67%) from muscle and exceeded the 2% predicted from energy intake-expenditure balance. Some immunological and lipid metabolic changes occurred, of uncertain mechanism or significance. OE II was unique in the diversity and complexity of studies carried out on a single, courageous cohort of subjects. These studies could never have been carried out in the field, and thus complement studies such as the American Medical Research Expedition to Everest (AMREE) that, although more limited in scope, serve as benchmarks and reality checks for chamber studies like OE II.

Fractal rigidity by enhanced sympatho-vagal antagonism in heartbeat interval dynamics elicited by central application of corticotropin-releasing factor in mice

The dynamics of heartbeat interval fluctuations were studied in awake unrestrained mice following intracerebroventricular application of the neuropeptide corticotropin-releasing factor (CRF). The cardiac time series derived from telemetric ECG monitoring were analyzed by non-parametric techniques of nonlinear signal processing: delay-vector variance (DVV) analysis, higher-order variability (HOV) analysis, empirical mode decomposition (EMD), multiscale embedding-space decomposition (MESD), multiexponent multifractal (MEMF) analysis. The analyses support the conjecture that cardiac dynamics of normal control mice has both deterministic and stochastic elements, is nonstationary, nonlinear, and exerts multifractal properties. Central application of CRF results in bradycardia and increased variability of the beat-to-beat fluctuations. The altered dynamical properties elicited by CRF reflect a significant loss of intrinsic structural complexity of cardiac control which is due to central neuroautonomic hyperexcitation, i.e., enhanced sympatho-vagal antagonism. The change in dynamical complexity is characterized by an effect referred to as fractal rigidity, leading to a significant impairment of adaptability to extrinsic challenges in a fluctuating environment. The impact of dynamical neurocardiopathy as a major precipiting factor for the propensity of cardiac arrhythmias or sudden cardiac death by unchecked central CRF release in significant acute life events in man is critically discussed.

Effect of cardiac vagal outflow on complexity and fractal correlation properties of heart rate dynamics

1. Cardiac vagal outflow is the major factor determining the magnitude of heart rate (HR) variability analysed by traditional time and frequency domain methods. New analysis techniques, such as fractal and complexity methods, have been developed to probe non-linear features in HR behaviour that may not be detectable by traditional methods. 2. We investigated the effects of vagal blockade (glycopyrrolate i.v. 5 microg kg-1 h-1 for 2 h, n = 8 vs. unmedicated control group, n = 8) and various breathing patterns (n = 12) on two non-linear measures of HR variability--detrended fluctuation analysis (DFA) and approximate entropy (ApEn)--in healthy male volunteers. 3. Glycopyrrolate decreased the mean (+/-SD) ApEn from 1.46 +/- 0.18 to 0.85 +/- 0.24 (P = 0.001 in comparison with the control group), and increased the short-term (alpha 1) and intermediate-term (alpha 2) fractal scaling exponents of DFA, alpha 1 from 0.96 +/- 0.19 to 1.43 +/- 0.29 (P = 0.003) and alpha 2 from 1.13 +/- 0.10 to 1.34 +/- 0.14 (P < 0.001). 4. Decrease in fixed respiration rate from 15 to 6 breaths min-1 increased alpha 1 from 0.83 +/- 0.25 to 1.18 +/- 0.27 (P < 0.001), but decreased alpha 2 from 0.88 +/- 0.09 to 0.45 +/- 0.17 (P < 0.001) and ApEn from 1.26 +/- 0.12 to 1.10 +/- 0.14 (P = 0.028). Rapid breathing (24 min-1) had no influence on these non-linear measures of HR variability. Hyperventilation (15 min-1, tidal volume increased voluntarily by 0.5 l) decreased alpha 1 from 0.83 +/- 0.25 to 0.66 +/- 0.28 (P = 0.002) but did not affect alpha 2 or ApEn. 5. To conclude, vagal blockade alters the fractal scaling properties of R-R intervals (alpha 1, alpha 2) and reduces the complexity (ApEn) of HR behaviour. Both the fractal and complexity measures of HR variability can also be influenced by changes in the breathing pattern.

From 1/f noise to multifractal cascades in heartbeat dynamics

We explore the degree to which concepts developed in statistical physics can be usefully applied to physiological signals. We illustrate the problems related to physiologic signal analysis with representative examples of human heartbeat dynamics under healthy and pathologic conditions. We first review recent progress based on two analysis methods, power spectrum and detrended fluctuation analysis, used to quantify long-range power-law correlations in noisy heartbeat fluctuations. The finding of power-law correlations indicates presence of scale-invariant, fractal structures in the human heartbeat. These fractal structures are represented by self-affine cascades of beat-to-beat fluctuations revealed by wavelet decomposition at different time scales. We then describe very recent work that quantifies multifractal features in these cascades, and the discovery that the multifractal structure of healthy dynamics is lost with congestive heart failure. The analytic tools we discuss may be used on a wide range of physiologic signals. (c) 2001 American Institute of Physics.

Effects of exercise and passive head-up tilt on fractal and complexity properties of heart rate dynamics

tk;1Passive head-up tilt and exercise result in specific changes in the spectral characteristics of heart rate (HR) variability as a result of reduced vagal and enhanced sympathetic outflow. Recently analytic methods based on nonlinear system theory have been developed to characterize the nonlinear features in HR dynamics. This study was designed to assess the changes in the fractal and complexity measures of HR behavior during the passive head-up tilt and during exercise. Fractal exponent (alpha(1)) and approximate entropy (ApEn), measures of short-term correlation properties and overall complexity of HR, respectively, along with spectral components of HR variability were analyzed during a passive head-up tilt test (n = 10) and a low-intensity steady-state exercise (n = 20) in healthy subjects. We observed that alpha(1) increased during the tilt test (from 0.85 +/- 0.22 to 1.48 +/- 0.20; P < 0.001) and during the exercise (from 1.00 +/- 0.22 to 1.37 +/- 0. 14; P < 0.001). ApEn also increased during the exercise (from 1.04 +/- 0.11 to 1. 11 +/- 0.08; P < 0.05), but it did not change during the tilt test. The normalized high-frequency spectral component decreased and the low-frequency component increased similarly during both the exercise and the tilt test (P < 0.001 for all). Exercise and passive tilt result in an increase of short-term fractal correlation properties of HR dynamics, which is related to changes in the balance between the low- and high-frequency oscillations in controlled situations. Overall complexity of HR dynamics increases during exercise but not during passive tilt.

Frequency domain analysis of heart rate variability in horses at rest and during exercise

The pattern of variation in heart rate on a beat-to-beat basis contains information concerning sympathetic (SNS) and parasympathetic (PNS) contributions to autonomic nervous system (ANS) modulation of heart rate (HR). In the present study, heart period (RR interval) time series data were collected at rest and during 3 different treadmill exercise protocols from 6 Thoroughbred horses. Frequency and spectral power were determined in 3 frequency bands: very low (VLF) 0-< or = 0.01, low (LO) >0.01-< or = 0.07 and high (HI) >0.07-< or = 0.5 cycles/beat. Indicators of sympathetic (SNSI = LO/HI) and parasympathetic (PNSI = HI/TOTAL) activity were calculated. Power in all bands fell progressively with increasing exercise intensity from rest to trot. At the gallop VLF and LO power continued to fall but HI power rose. SNSI rose from rest to walk, then fell with increasing effort and was lowest at the gallop. PNSI fell from rest to walk, then rose and was highest at the gallop. Normalised HI power exceeded combined VLF and LO power at all gaits, with the ratio HI to LO power being lowest at the walk and highest at the gallop. ANS indicators showed considerable inter-horse variation, and varied less consistently than raw power with increasing physical effort. In the horses studied, the relationship between power and HR changed at exercise intensities associated with heart rates above approximately 120-130 beats/min. At this level, humoral and other non-neural mechanisms may become more important than autonomic modulation in influencing heart rate and heart rate variability (HRV). HRV at intense effort may be influenced by respiratory-gait entrainment, energetics of locomotion and work of breathing. HRV analysis in the frequency domain would appear to be of potential value as a noninvasive means of assessing autonomic modulation of heart rate at low exercise intensities, only. The technique may be a sensitive method for assessing exercise response to experimental manipulations and disease states.

Even slight movements disturb analysis of cardiovascular dynamics

We hypothesized that spontaneous movements (postural adjustments and ideomotion) disturb analysis of heart rate and blood pressure variability and could explain the discrepancy between studies. We measured R-R intervals and systolic blood pressure in nine healthy sitting subjects during three protocols: 1) no movement allowed, 2) movements allowed but not standing, 3) movements and standing allowed. Heart rate and blood pressure were not altered by movements. Movements with or without standing produced a twofold or greater increase of the overall variability of R-R intervals and of the low-frequency components of spectral analysis of heart rate variability. The spectral exponent beta of heart rate variability (1. 123 at rest) was changed by movements (1.364), and the percentage of fractal noise (79% at rest) was increased by standing (91%, coarse-graining spectral analysis). Spontaneous movements could induce a plateau in the correlation dimensions of heart rate variability, but they changed its nonlinear predictability. We suggest that future studies on short-term cardiovascular variability should control spontaneous movements.

Multifractality in human heartbeat dynamics

There is evidence that physiological signals under healthy conditions may have a fractal temporal structure. Here we investigate the possibility that time series generated by certain physiological control systems may be members of a special class of complex processes, termed multifractal, which require a large number of exponents to characterize their scaling properties. We report on evidence for multifractality in a biological dynamical system, the healthy human heartbeat, and show that the multifractal character and nonlinear properties of the healthy heart rate are encoded in the Fourier phases. We uncover a loss of multifractality for a life-threatening condition, congestive heart failure.

Is breathing in infants chaotic? Dimension estimates for respiratory patterns during quiet sleep

We describe an analysis of dynamic behavior apparent in times-series recordings of infant breathing during sleep. Three principal techniques were used: estimation of correlation dimension, surrogate data analysis, and reduced linear (autoregressive) modeling (RARM). Correlation dimension can be used to quantify the complexity of time series and has been applied to a variety of physiological and biological measurements. However, the methods most commonly used to estimate correlation dimension suffer from some technical problems that can produce misleading results if not correctly applied. We used a new technique of estimating correlation dimension that has fewer problems. We tested the significance of dimension estimates by comparing estimates with artificial data sets (surrogate data). On the basis of the analysis, we conclude that the dynamics of infant breathing during quiet sleep can best be described as a nonlinear dynamic system with large-scale, low-dimensional and small-scale, high-dimensional behavior; more specifically, a noise-driven nonlinear system with a two-dimensional periodic orbit. Using our RARM technique, we identified the second period as cyclic amplitude modulation of the same period as periodic breathing. We conclude that our data are consistent with respiration being chaotic.

Stability of heartbeat interval distributions in chronic high altitude hypoxia

Recent studies of nonlinear dynamics of the long-term variability of heart rate have identified nontrivial long-range correlations and scale-invariant power-law characteristics (l/f noise) that were remarkably consistent between individuals and were unrelated to external or environmental stimuli (Meyer et al., 1998a). The present analysis of complex nonstationary heartbeat patterns is based on the sequential application of the wavelet transform for elimination of local polynomial nonstationary behavior and an analytic signal approach by use of the Hilbert transform (Cumulative Variation Amplitude Analysis). The effects of chronic high altitude hypoxia on the distributions and scaling functions of cardiac intervals over 24 hr epochs and 4 hr day/nighttime subepochs were determined from serial heartbeat interval time series of digitized 24 hr ambulatory ECGs recorded in 9 healthy subjects (mean age 34 yrs) at sea level and during a sojourn at high altitude (5,050 m) for 34 days (Ev-K2-CNR Pyramid Laboratory, Sagarmatha National Park, Nepal). The results suggest that there exists a hidden, potentially universal, common structure in the heterogeneous time series. A common scaling function with a stable Gamma distribution defines the probability density of the amplitudes of the fluctuations in the heartbeat interval time series of individual subjects. The appropriately rescaled distributions of normal subjects at sea level demonstrated stable Gamma scaling consistent with a single scaled plot (data collapse). Longitudinal assessment of the rescaled distributions of the 24 hr recordings of individual subjects showed that the stability of the distributions was unaffected by the subject's exposure to a hypobaric (hypoxic) environment. The rescaled distributions of 4 hr subepochs showed similar scaling behavior with a stable Gamma distribution indicating that the common structure was unequivocally applicable to both day and night phases and, furthermore, did not undergo systematic changes in response to high altitude. In contrast, a single function stable over a wide range of time scales was not observed in patients with congestive heart failure or patients after cardiac transplantation. The functional form of the scaling in normal subjects would seem to be attributable to the underlying nonlinear dynamics of cardiac control. The results suggest that the observed Gamma scaling of the distributions in healthy subjects constitutes an intrinsic dynamical property of normal heart function that would not undergo early readjustment or late acclimatization to extrinsic environmental physiological stress, e.g., chronic hypoxia.

Is the heart preadapted to hypoxia? Evidence from fractal dynamics of heartbeat interval fluctuations at high altitude (5,050 m)

The dynamics of heartbeat interval time series over large time scales were studied by a modified random walk analysis introduced recently as Detrended Fluctuation Analysis. In this analysis, the intrinsic fractal long-range power-law correlation properties of beat-to-beat fluctuations generated by the dynamical system (i.e., cardiac rhythm generator), after decomposition from extrinsic uncorrelated sources, can be quantified by the scaling exponent (alpha) which, in healthy subjects, for time scales of approximately 10(4) beats is approximately 1.0. The effects of chronic hypoxia were determined from serial heartbeat interval time series of digitized twenty-four-hour ambulatory ECGs recorded in nine healthy subjects (mean age thirty-four years old) at sea level and during a sojourn at 5,050 m for thirty-four days (EvK2-CNR Pyramid Laboratory, Sagarmatha National Park, Nepal). The group averaged alpha exponent (+/- SD) was 0.99 +/- 0.04 (range 0.93-1.04). Longitudinal assessment of alpha in individual subjects did not reveal any effect of exposure to chronic high altitude hypoxia. The finding of alpha approximately 1 indicating scale-invariant long-range power-law correlations (1/f noise) of heartbeat fluctuations would reflect a genuinely self-similar fractal process that typically generates fluctuations on a wide range of time scales. Lack of a characteristic time scale along with the absence of any effect from exposure to chronic hypoxia on scaling properties suggests that the neuroautonomic cardiac control system is preadapted to hypoxia which helps prevent excessive mode-locking (error tolerance) that would restrict its functional responsiveness (plasticity) to hypoxic or other physiological stimuli.

Experimental human endotoxemia increases cardiac regularity: results from a prospective, randomized, crossover trial

OBJECTIVE

To determine whether human endotoxemia is associated with a loss of the physiologic beat-to-beat variability of heart rate.

DESIGN

Prospective, randomized, crossover, single-blind study.

SETTING

Clinical research center in a federal, nonuniversity hospital.

SUBJECTS

Healthy volunteers.

INTERVENTIONS

Intravenous administration of reference (Escherichia coli) endotoxin or saline placebo, with or without previous administration of oral ibuprofen.

MEASUREMENTS AND MAIN RESULTS

Electrocardiograms were continuously recorded and digitized using series of 1000 beat epochs of R-R intervals over 8 hrs. Analyses included measures in the time domain (standard deviation), frequency domain (power spectra), and a measure of regularity (approximate entropy). Endotoxin administration was associated with loss of variability by all measures. This loss of variability remained significant even with administration of ibuprofen, which blocked the development of fever and endotoxin-related symptoms.

CONCLUSIONS

Infusion of endotoxin into human volunteers causes loss of heart rate variability, as measured by standard deviation and power spectra, as well as an increase in heart rate regularity, as measured by approximate entropy. Changes in approximate entropy occurred earlier than changes in other heart rate variability measures and may be a useful means of detecting early sepsis. This reduction in regularity is consistent with a model in which the pathogenesis of multiple organ system dysfunction syndrome involves the physiologic uncoupling of vital organ systems.

Left-insular cortex lesions perturb cardiac autonomic tone in humans

The insular cortex is involved in cardiac regulation. The left insula is predominantly responsible for parasympathetic cardiovascular effects. Damage to this area could shift cardiovascular balance towards increased basal sympathetic tone (a pro-arrhythmic condition) and contribute to the excess cardiac mortality following stroke. Acute left insular stroke increased basal cardiac sympathetic tone and was associated with a decrease in randomness of heart rate variability. In addition, phase relationships between heart rate and blood pressure were disturbed, implying a disruption of oscillators involved in cardiovascular control. The insula appears to be involved in human heart rate regulation and damage to it may encourage a pro-arrhythmic state.

Heart rate and respiratory rhythm dynamics on ascent to high altitude

OBJECTIVE

To investigate the alterations in autonomic control of heart rate at high altitude and to test the hypothesis that hypoxaemic stress during exposure to high altitude induces non-linear, periodic heart rate oscillations, similar to those seen in heart failure and the sleep apnoea syndrome.

SUBJECTS

11 healthy subjects aged 24-64.

MAIN OUTCOME MEASURES

24 hour ambulatory electrocardiogram records obtained at baseline (1524 m) and at 4700 m. Simultaneous heart rate and respiratory dynamics during 2.5 hours of sleep by fast Fourier transform analysis of beat to beat heart rate and of an electrocardiographically derived respiration signal.

RESULTS

All subjects had resting hypoxaemia at high altitude, with an average oxyhaemoglobin saturation of 81% (5%). There was no significant change in mean heart rate, but low frequency (0.01-0.05 Hz) spectral power was increased (P < 0.01) at high altitude. Time series analysis showed a complex range of non-linear sinus rhythm dynamics. Striking low frequency (0.04-0.06 Hz) heart rate oscillations were observed during sleep in eight subjects at high altitude. Analysis of the electrocardiographically derived respiration signal indicated that these heart rate oscillations correlated with low frequency respiratory oscillations.

CONCLUSIONS

These data suggest (a) that increased low frequency power during high altitude exposure is not simply attributable to increased sympathetic modulation of heart rate, but relates to distinctive cardiopulmonary oscillations at approximately 0.05 Hz and (b) that the emergence of periodic heart rate oscillations at high altitude is consistent with an unstable cardiopulmonary control system that may develop on acute exposure to hypoxaemic stress.

Autonomic nervous control of heart rate at altitude (5050 m)

To investigate possible changes in autonomic regulation of heart rate as a result of acclimatization to high altitude, indexes of autonomic nervous activity were obtained non invasively by spectrum analysis of heart rate variability on five healthy male subjects [age, 31 (SEM 2) years] during a postural change from supine to seated, both at sea level and after 1 month of exposure to an altitude of 5050 m. Heart rate fluctuations at the respiratory frequency (high frequency, HF) are mediated by the parasympathetic system whereas fluctuations at about 0.1 Hz (low frequency, LF) are due to both sympathetic and parasympathetic nervous systems. Maximal heart rate, as measured during an incremental exercise test, decreased from 184 (SEM 5) beats.min-1 at sea level to 152 (SEM 2) beats.min-1 at 5050 m. At sea level, the change in posture from supine to seated induced an increase in LF amplitude accompanied by an increase or a decrease in HF amplitude, whereas after 1 month at altitude the HF amplitude decreased in all subjects, with little or no change in LF amplitude. These results indicate a changed strategy of heart rate regulation after acclimatization to high altitude. At sea level, the postural change induced an increase in sympathetic activity in all subjects with different individual vagal responses, whereas at altitude the postural change induced a net decrease in vagal tone in all subjects, with little or no change in sympathetic activity. These results corroborate the reported reduced sensitivity of the heart to adrenergic drive in chronic hypoxia, which may, at least in part, explain the decreased maximal heart rate in altitude-acclimatized human subjects.