Search NASA⌕ Search

Engineering topics

Goldberger, A. L.

Publications and source records attributed to Goldberger, A. L..

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Marked exacerbation of orthostatic intolerance after long- vs. short-duration spaceflight in veteran astronauts

OBJECTIVE: The incidence of postflight orthostatic intolerance after short-duration spaceflight is about 20%. However, the incidence after long-duration spaceflight was unknown. The purpose of this study was to test the hypothesis that orthostatic intolerance is more severe after long-duration than after short-duration flight. METHODS: We performed tilt tests on six astronauts before and after long-duration (129-190 days) spaceflights and compared these data with data obtained during stand tests before and after previous short-duration missions. RESULTS: Five of the six astronauts studied became presyncopal during tilt testing after long-duration flights. Only one had become presyncopal during stand testing after short-duration flights. We also compared the long-duration flight tilt test data to tilt test data from 20 different astronauts who flew on the short-duration Shuttle missions that delivered and recovered the astronauts to and from the Mir Space Station. Five of these 20 astronauts became presyncopal on landing day. Heart rate responses to tilt were no different between astronauts on long-duration flights and astronauts on short-duration flights, but long-duration subjects had lower stroke volumes and cardiac outputs than short-duration presyncopal subjects, suggesting a possible decrease in cardiac contractile function. One subject had subnormal norepinephrine release with upright posture after the long flight but not after the short flight. Plasma volume losses were not greater after long flights. CONCLUSION: Long-duration spaceflight markedly increases orthostatic intolerance, probably with multiple contributing factors.

STS Shuttle Project↗
NASA NTRS2001

Noise effects on the complex patterns of abnormal heartbeats

Patients at high risk for sudden death often exhibit complex heart rhythms in which abnormal heartbeats are interspersed with normal heartbeats. We analyze such a complex rhythm in a single patient over a 12-h period and show that the rhythm can be described by a theoretical model consisting of two interacting oscillators with stochastic elements. By varying the magnitude of the noise, we show that for an intermediate level of noise, the model gives best agreement with key statistical features of the dynamics.

NASA Discipline Cardiopulmonary↗
NASA NTRS2001

Magnitude and sign correlations in heartbeat fluctuations

We propose an approach for analyzing signals with long-range correlations by decomposing the signal increment series into magnitude and sign series and analyzing their scaling properties. We show that signals with identical long-range correlations can exhibit different time organization for the magnitude and sign. We find that the magnitude series relates to the nonlinear properties of the original time series, while the sign series relates to the linear properties. We apply our approach to the heartbeat interval series and find that the magnitude series is long-range correlated, while the sign series is anticorrelated and that both magnitude and sign series may have clinical applications.

NASA Discipline Cardiopulmonary↗
NASA NTRS2000

Holter monitoring: are two days better than one?

The optimal duration of Holter monitoring (HM) to minimize costs and maximize yield is unknown. In a retrospective review of 164 patients referred to a tertiary care center for evaluation with 2 days of HM, we found that 48 hours was not cost effective when compared with the traditional 24-hour period.

NASA Discipline Cardiopulmonary↗
NASA NTRS2000

Dynamic markers of altered gait rhythm in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a disorder marked by loss of motoneurons. We hypothesized that subjects with ALS would have an altered gait rhythm, with an increase in both the magnitude of the stride-to-stride fluctuations and perturbations in the fluctuation dynamics. To test for this locomotor instability, we quantitatively compared the gait rhythm of subjects with ALS with that of normal controls and with that of subjects with Parkinson's disease (PD) and Huntington's disease (HD), pathologies of the basal ganglia. Subjects walked for 5 min at their usual pace wearing an ankle-worn recorder that enabled determination of the duration of each stride and of stride-to-stride fluctuations. We found that the gait of patients with ALS is less steady and more temporally disorganized compared with that of healthy controls. In addition, advanced ALS, HD, and PD were associated with certain common, as well as apparently distinct, features of altered stride dynamics. Thus stride-to-stride control of gait rhythm is apparently compromised with ALS. Moreover, a matrix of markers based on gait dynamics may be useful in characterizing certain pathologies of motor control and, possibly, in quantitatively monitoring disease progression and evaluating therapeutic interventions.

NASA Program Biomedical Research and Countermeasur↗
NASA NTRS2000

Oxygen desaturations triggered by partial seizures: implications for cardiopulmonary instability in epilepsy

PURPOSE: The occurrence of hypoxemia in adults with partial seizures has not been systematically explored. Our aim was to study in detail the temporal dynamics of this specific type of ictal-associated hypoxemia. METHODS: During long-term video/EEG monitoring (LTM), patients underwent monitoring of oxygen saturation using a digital Spo2 (pulse oximeter) transducer. Six patients (nine seizures) were identified with oxygen desaturations after the onset of partial seizure activity. RESULTS: Complex partial seizures originated from both left and right temporal lobes. Mean seizure duration (+/-SD) was 73 +/- 18 s. Mean Spo2 desaturation duration was 76 +/- 19 s. The onset of oxygen desaturation followed seizure onset with a mean delay of 43 +/- 16 s. Mean (+/-SD) Spo2 nadir was 83 +/- 5% (range, 77-91%), occurring an average of 35 +/- 12 s after the onset of the desaturation. One seizure was associated with prolonged and recurrent Spo2 desaturations. CONCLUSIONS: Partial seizures may be associated with prominent oxygen desaturations. The comparable duration of each seizure and its subsequent desaturation suggests a close mechanistic (possibly causal) relation. Spo2 monitoring provides an added means for seizure detection that may increase LTM yield. These observations also raise the possibility that ictal ventilatory dysfunction could play a role in certain cases of sudden unexpected death in epilepsy in adults with partial seizures.

NASA Program Biomedical Research and Countermeasur↗
NASA NTRS2000

Fractal correlation properties of R-R interval dynamics and mortality in patients with depressed left ventricular function after an acute myocardial infarction

BACKGROUND: Preliminary data suggest that the analysis of R-R interval variability by fractal analysis methods may provide clinically useful information on patients with heart failure. The purpose of this study was to compare the prognostic power of new fractal and traditional measures of R-R interval variability as predictors of death after acute myocardial infarction. METHODS AND RESULTS: Time and frequency domain heart rate (HR) variability measures, along with short- and long-term correlation (fractal) properties of R-R intervals (exponents alpha(1) and alpha(2)) and power-law scaling of the power spectra (exponent beta), were assessed from 24-hour Holter recordings in 446 survivors of acute myocardial infarction with a depressed left ventricular function (ejection fraction </=35%). During a mean+/-SD follow-up period of 685+/-360 days, 114 patients died (25.6%), with 75 deaths classified as arrhythmic (17.0%) and 28 as nonarrhythmic (6.3%) cardiac deaths. Several traditional and fractal measures of R-R interval variability were significant univariate predictors of all-cause mortality. Reduced short-term scaling exponent alpha(1) was the most powerful R-R interval variability measure as a predictor of all-cause mortality (alpha(1) <0.75, relative risk 3.0, 95% confidence interval 2.5 to 4.2, P<0.001). It remained an independent predictor of death (P<0.001) after adjustment for other postinfarction risk markers, such as age, ejection fraction, NYHA class, and medication. Reduced alpha(1) predicted both arrhythmic death (P<0.001) and nonarrhythmic cardiac death (P<0.001). CONCLUSIONS: Analysis of the fractal characteristics of short-term R-R interval dynamics yields more powerful prognostic information than the traditional measures of HR variability among patients with depressed left ventricular function after an acute myocardial infarction.

Non-NASA Center↗
NASA NTRS2000

[Individual peculiarities of adaptation to long-term space flights: 24-hour heart rhythm monitoring]

Presented are results of studying 24-hr variability of the cardiac rhythm which characterizes individual difference in reactions of two crew members to the same set of stresses during a 115-day MIR mission. Spacelab (USA) cardiorecorders were used. Data of monitoring revealed significantly different baseline health statuses of the cosmonauts. These functional differences were also observed in the mission. In one of the cosmonauts, the cardiac regulation changed over to a more economic functioning with the autonomous balance shifted towards enhanced sympathetic activity. After 2-3 months on mission he had almost recovered pre-launch level of regulation. In the other, the regulatory system was appreciably strained at the beginning of the mission as compared with preflight baseline. Later on, on flight months 2-3, this strain kept growing till a drastic depletion of the functional reserve. On return to Earth, this was manifested by a strong stress reaction with a sharp decline in power of high-frequency and grow in power of very low frequency components of the heart rhythm. The data suggest that adaptation to space flight and reactions in the readaptation period are dependent on initial health status of crew members, and functional reserve.

long duration↗
NASA NTRS1999

Sleep-wake differences in scaling behavior of the human heartbeat: analysis of terrestrial and long-term space flight data

We compare scaling properties of the cardiac dynamics during sleep and wake periods for healthy individuals, cosmonauts during orbital flight, and subjects with severe heart disease. For all three groups, we find a greater degree of anticorrelation in the heartbeat fluctuations during sleep compared to wake periods. The sleep-wake difference in the scaling exponents for the three groups is comparable to the difference between healthy and diseased individuals. The observed scaling differences are not accounted for simply by different levels of activity, but appear related to intrinsic changes in the neuroautonomic control of the heartbeat.

Flight Experiment↗
NASA NTRS1999

Scaling in nature: from DNA through heartbeats to weather

The purpose of this report is to describe some recent progress in applying scaling concepts to various systems in nature. We review several systems characterized by scaling laws such as DNA sequences, heartbeat rates and weather variations. We discuss the finding that the exponent alpha quantifying the scaling in DNA in smaller for coding than for noncoding sequences. We also discuss the application of fractal scaling analysis to the dynamics of heartbeat regulation, and report the recent finding that the scaling exponent alpha is smaller during sleep periods compared to wake periods. We also discuss the recent findings that suggest a universal scaling exponent characterizing the weather fluctuations.

Review↗
NASA NTRS1999

Statistical physics and physiology: monofractal and multifractal approaches

Even under healthy, basal conditions, physiologic systems show erratic fluctuations resembling those found in dynamical systems driven away from a single equilibrium state. Do such "nonequilibrium" fluctuations simply reflect the fact that physiologic systems are being constantly perturbed by external and intrinsic noise? Or, do these fluctuations actually, contain useful, "hidden" information about the underlying nonequilibrium control mechanisms? We report some recent attempts to understand the dynamics of complex physiologic fluctuations by adapting and extending concepts and methods developed very recently in statistical physics. Specifically, we focus on interbeat interval variability as an important quantity to help elucidate possibly non-homeostatic physiologic variability because (i) the heart rate is under direct neuroautonomic control, (ii) interbeat interval variability is readily measured by noninvasive means, and (iii) analysis of these heart rate dynamics may provide important practical diagnostic and prognostic information not obtainable with current approaches. The analytic tools we discuss may be used on a wider range of physiologic signals. We first review recent progress using two analysis methods--detrended fluctuation analysis and wavelets--sufficient for quantifying monofractual structures. We then describe recent work that quantifies multifractal features of interbeat interval series, and the discovery that the multifractal structure of healthy subjects is different than that of diseased subjects.

NASA Discipline Cardiopulmonary↗
NASA NTRS1999

Cardiac interbeat interval dynamics from childhood to senescence : comparison of conventional and new measures based on fractals and chaos theory

BACKGROUND: New methods of R-R interval variability based on fractal scaling and nonlinear dynamics ("chaos theory") may give new insights into heart rate dynamics. The aims of this study were to (1) systematically characterize and quantify the effects of aging from early childhood to advanced age on 24-hour heart rate dynamics in healthy subjects; (2) compare age-related changes in conventional time- and frequency-domain measures with changes in newly derived measures based on fractal scaling and complexity (chaos) theory; and (3) further test the hypothesis that there is loss of complexity and altered fractal scaling of heart rate dynamics with advanced age. METHODS AND RESULTS: The relationship between age and cardiac interbeat (R-R) interval dynamics from childhood to senescence was studied in 114 healthy subjects (age range, 1 to 82 years) by measurement of the slope, beta, of the power-law regression line (log power-log frequency) of R-R interval variability (10(-4) to 10(-2) Hz), approximate entropy (ApEn), short-term (alpha(1)) and intermediate-term (alpha(2)) fractal scaling exponents obtained by detrended fluctuation analysis, and traditional time- and frequency-domain measures from 24-hour ECG recordings. Compared with young adults (<40 years old, n=29), children (<15 years old, n=27) showed similar complexity (ApEn) and fractal correlation properties (alpha(1), alpha(2), beta) of R-R interval dynamics despite lower spectral and time-domain measures. Progressive loss of complexity (decreased ApEn, r=-0.69, P<0.001) and alterations of long-term fractal-like heart rate behavior (increased alpha(2), r=0.63, decreased beta, r=-0.60, P<0.001 for both) were observed thereafter from middle age (40 to 60 years, n=29) to old age (>60 years, n=29). CONCLUSIONS: Cardiac interbeat interval dynamics change markedly from childhood to old age in healthy subjects. Children show complexity and fractal correlation properties of R-R interval time series comparable to those of young adults, despite lower overall heart rate variability. Healthy aging is associated with R-R interval dynamics showing higher regularity and altered fractal scaling consistent with a loss of complex variability.

NASA Discipline Cardiopulmonary↗
NASA NTRS1999

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.

Non-NASA Center↗
NASA NTRS1999

Heart rate dynamics before spontaneous onset of ventricular fibrillation in patients with healed myocardial infarcts

The traditional methods of analyzing heart rate (HR) variability have failed to predict imminent ventricular fibrillation (VF). We sought to determine whether new methods of analyzing RR interval variability based on nonlinear dynamics and fractal analysis may help to detect subtle abnormalities in RR interval behavior before the onset of life-threatening arrhythmias. RR interval dynamics were analyzed from 24-hour Holter recordings of 15 patients who experienced VF during electrocardiographic recording. Thirty patients without spontaneous or inducible arrhythmia events served as a control group in this retrospective case control study. Conventional time- and frequency-domain measurements, the short-term fractal scaling exponent (alpha) obtained by detrended fluctuation analysis, and the slope (beta) of the power-law regression line (log power - log frequency, 10(-4)-10(-2) Hz) of RR interval dynamics were determined. The short-term correlation exponent alpha of RR intervals (0.64 +/- 0.19 vs 1.05 +/- 0.12; p <0.001) and the power-law slope beta (-1.63 +/- 0.28 vs -1.31 +/- 0.20, p <0.001) were lower in the patients before the onset of VF than in the control patients, but the SD and the low-frequency spectral components of RR intervals did not differ between the groups. The short-term scaling exponent performed better than any other measurement of HR variability in differentiating between the patients with VF and controls. Altered fractal correlation properties of HR behavior precede the spontaneous onset of VF. Dynamic analysis methods of analyzing RR intervals may help to identify abnormalities in HR behavior before VF.

Non-NASA Center↗
NASA NTRS1999

Fractal analysis of heart rate dynamics as a predictor of mortality in patients with depressed left ventricular function after acute myocardial infarction. TRACE Investigators. TRAndolapril Cardiac Evaluation

A number of new methods have been recently developed to quantify complex heart rate (HR) dynamics based on nonlinear and fractal analysis, but their value in risk stratification has not been evaluated. This study was designed to determine whether selected new dynamic analysis methods of HR variability predict mortality in patients with depressed left ventricular (LV) function after acute myocardial infarction (AMI). Traditional time- and frequency-domain HR variability indexes along with short-term fractal-like correlation properties of RR intervals (exponent alpha) and power-law scaling (exponent beta) were studied in 159 patients with depressed LV function (ejection fraction <35%) after an AMI. By the end of 4-year follow-up, 72 patients (45%) had died and 87 (55%) were still alive. Short-term scaling exponent alpha (1.07 +/- 0.26 vs 0.90 +/- 0.26, p <0.001) and power-law slope beta (-1.35 +/- 0.23 vs -1.44 +/- 0.25, p <0.05) differed between survivors and those who died, but none of the traditional HR variability measures differed between these groups. Among all analyzed variables, reduced scaling exponent alpha (<0.85) was the best univariable predictor of mortality (relative risk 3.17, 95% confidence interval 1.96 to 5.15, p <0.0001), with positive and negative predictive accuracies of 65% and 86%, respectively. In the multivariable Cox proportional hazards analysis, mortality was independently predicted by the reduced exponent alpha (p <0.001) after adjustment for several clinical variables and LV function. A short-term fractal-like scaling exponent was the most powerful HR variability index in predicting mortality in patients with depressed LV function. Reduction in fractal correlation properties implies more random short-term HR dynamics in patients with increased risk of death after AMI.

Non-NASA Center↗
NASA NTRS1999

Analysis of the ST-T complex of the electrocardiogram using the Karhunen--Loeve transform: adaptive monitoring and alternans detection

The Karhunen-Loeve transform (KLT) is applied to study the ventricular repolarisation period as reflected in the ST-T complex of the surface ECG. The KLT coefficients provide a sensitive means of quantitating ST-T shapes. A training set of ST-T complexes is used to derive a set of KLT basis vectors that permits representation of 90% of the signal energy using four KLT coefficients. As a truncated KLT expansion tends to favor representation of the signal over any additive noise, a time series of KLT coefficients obtained from successive ST-T complexes is better suited for representation of both medium-term variations (such as ischemic changes) and short-term variations (such as ST-T alternans) than discrete parameters such as the ST level or other local indices. For analysis of ischemic changes, an adaptive filter is described that can be used to estimate the KLT coefficient, yielding an increase in the signal-to-noise ratio of 10 dB (u = 0.1), with a convergence time of about three beats. A beat spectrum of the unfiltered KLT coefficient series is used for detection of ST-T alterans. These methods are illustrated with examples from the European ST-T Database. About 20% of records revealed quasi-periodic salvos of ischemic ST-T change episodes and another 20% exhibit repetitive, but not clearly periodic patterns of ST-T change episodes. About 5% of ischemic episodes were associated with ST-T alterans.

NASA Discipline Cardiopulmonary↗
NASA NTRS1999

Scaling features of noncoding DNA

We review evidence supporting the idea that the DNA sequence in genes containing noncoding regions is correlated, and that the correlation is remarkably long range--indeed, base pairs thousands of base pairs distant are correlated. We do not find such a long-range correlation in the coding regions of the gene, and utilize this fact to build a Coding Sequence Finder Algorithm, which uses statistical ideas to locate the coding regions of an unknown DNA sequence. Finally, we describe briefly some recent work adapting to DNA the Zipf approach to analyzing linguistic texts, and the Shannon approach to quantifying the "redundancy" of a linguistic text in terms of a measurable entropy function, and reporting that noncoding regions in eukaryotes display a larger redundancy than coding regions. Specifically, we consider the possibility that this result is solely a consequence of nucleotide concentration differences as first noted by Bonhoeffer and his collaborators. We find that cytosine-guanine (CG) concentration does have a strong "background" effect on redundancy. However, we find that for the purine-pyrimidine binary mapping rule, which is not affected by the difference in CG concentration, the Shannon redundancy for the set of analyzed sequences is larger for noncoding regions compared to coding regions.

Non-NASA Center↗