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Register a new userScaling and wavelet-based analyses of the long-term heart rate variability of the Eastern Oyster
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Added by
Pavel A. Ritto Mijangos
Publication date
2004
fields
Physics
and research's language is
English
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Characterisations of the long-term behaviour of heart rate variability in humans have emerged in the last few years as promising candidates to became clinically significant tools. We present two different statistical analyses of long time recordings of the heart rate variation in the Eastern Oyster. The circulatory system of this marine mollusk has important anatomical and physiological dissimilitudes in comparison to that of humans and it is exposed to dramatically different environmental influences. Our results resemble those previously obtained in humans. This suggests that in spite of the discrepancies, the mechanisms of long--term cardiac control on both systems share a common underlying dynamic.
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The heart beat data recorded from samples before and during meditation are analyzed using two different scaling analysis methods. These analyses revealed that mediation severely affects the long range correlation of heart beat of a normal heart. Moreover, it is found that meditation induces periodic behavior in the heart beat. The complexity of the heart rate variability is quantified using multiscale entropy analysis and recurrence analysis. The complexity of the heart beat during mediation is found to be more.
A tetra of sets which elements are time series of interbeats has been obtained from the databank Physionet-MIT-BIH, corresponding to the following failures at the humans heart: Obstructive Sleep Apnea, Congestive Heart Failure, and Atrial Fibrillation. Those times series has been analyzed statistically using an already known technique based on the Wavelet and Hilbert Transforms. That technique has been applied to the time series of interbeats for 87 patients, in order to find out the dynamics of the heart. The size of the times series varies around 7 to 24 h. while the kind of wavelet selected for this study has been any one of: Daubechies, Biortoghonal, and Gaussian. The analysis has been done for the complet set of scales ranging from: 1-128 heartbeats. Choosing the Biorthogonal wavelet: bior3.1, it is observed: (a) That the time series hasnt to be cutted in shorter periods, with the purpose to obtain the collapsing of the data, (b) An analytical, universal behavior of the data, for the first and second diseases, but not for the third.
In this work we study the characteristics of the heart rate variability (HRV) as a function of age and gender. The analyzed data include previous results reported in the literature. The data obtained in this work expand the range of age studied until now revealing new behaviors not reported before. We analyze some measurements in the time domain,in the frequency domain and nonlinear measurements. We report scaling behaviors and abrupt changes in some measurements. There is also a progressive decrease in the dimensionality of the dynamic system governing the HRV, with the increase in age that is interpreted in terms ofautonomic regulation of cardiac activity.
The bulk of available stellar activity observations is frequently checked for the manifestation of signs in comparison with the known characteristic of solar magnetic modulation. The problem is that stellar activity records are usually an order of magnitude shorter than available observations of solar activity variation. Therefore, the resolved time scales of stellar activity are insufficient to decide reliably that a cyclic variation for a particular star is similar to the well-known 11-yr sunspot cycles. As a result, recent studies report several stars with double or multiple cycles which serve to challenge the underlying theoretical understanding. This is why a consistent method to separate true cycles from stochastic variations is required. In this paper, we suggest that a conservative method, based on the best practice of wavelet analysis previously applied to the study of solar activity, for studying and interpreting the longest available stellar activity record - photometric monitoring of V833 Tau for more than 100 years. We find that the observed variations of V833 Tau with timescales of 2-50 yr should be comparable with the known quasi-periodic solar mid-term variations, whereas the true cycle of V833 Tau, if it exists, should be of about a century or even longer. We argue that this conclusion does not contradict the expectations from stellar dynamo theory.
The spectra of empirical correlation matrices, constructed from multivariate data, are widely used in many areas of sciences, engineering and social sciences as a tool to understand the information contained in typically large datasets. In the last two decades, random matrix theory-based tools such as the nearest neighbour eigenvalue spacing and eigenvector distributions have been employed to extract the significant modes of variability present in such empirical correlations. In this work, we present an alternative analysis in terms of the recently introduced spacing ratios, which does not require the cumbersome unfolding process. It is shown that the higher order spacing ratio distributions for the Wishart ensemble of random matrices, characterized by the Dyson index $beta$, is related to the first order spacing ratio distribution with a modified value of co-dimension $beta$. This scaling is demonstrated for Wishart ensemble and also for the spectra of empirical correlation matrices drawn from the observed stock market and atmospheric pressure data. Using a combination of analytical and numerics, such scalings in spacing distributions are also discussed.
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