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Influence of Progressive Central Hypovolemia on Hölder Exponent Distributions of Cardiac Interbeat Intervals

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Abstract

The purpose of the study was to determine the dependency of the statistical properties of the R to R interval (RRI) time series on progressive central hypovolemia with lower body negative pressure. Two data-processing techniques based on wavelet transforms were used to determine the change in the nonstationary nature of the RRI time series with changing negative pressure. The results suggest that autonomic neural mechanism driving cardiac interbeat intervals during central hypovolemia go through various levels of multifractality, as determined by Hölder exponent distributions.

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Authors and Affiliations

  1. Department of Physics, Duke University, Durham, NC 27708

    Bruce J. West & Nicola Scafetta

  2. Pratt School Electrical Engineering Department, Duke University, P.O. Box 90291, Durham, NC 27708

    Bruce J. West & Nicola Scafetta

  3. Mathematics Division, Army Research Office, Research Triangle Park, NC 27709

    Bruce J. West

  4. U.S. Army Institute of Surgical Research Fort Sam Houston, Texas, 78234

    William H. Cooke

  5. Istituto Fisiologia Clinica, CNR-Area Ricerca San Cataldo, Via Moruzzi 1, 56124-Pisa

    Rita Balocchi

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  1. Bruce J. West
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  2. Nicola Scafetta
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  3. William H. Cooke
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  4. Rita Balocchi
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West, B.J., Scafetta, N., Cooke, W.H. et al. Influence of Progressive Central Hypovolemia on Hölder Exponent Distributions of Cardiac Interbeat Intervals. Annals of Biomedical Engineering 32, 1077–1087 (2004). https://doi.org/10.1114/B:ABME.0000036644.69559.ad

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