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Complex Systems and Computational Biology Approaches to Acute Inflammation pp 79–99Cite as

Analysis of Ventilatory Pattern Variability

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Abstract

Each breath is not generated de novo; rather, the ventilatory pattern is a continuous oscillation in which the next breath is related to the present one; and being biologic, the ventilatory pattern varies. Further, the responsiveness of respiration to sensory input is dynamic because neural mechanisms scale afferent input. Thus, ventilatory pattern variability (VPV) has deterministic properties, which may vary in health and disease. We have developed analytical tools to distinguish and assess linear and nonlinear sources of VPV. Surrogate data sets obtained by shuffling the original data while preserving its amplitude distribution and autocorrelation function and, thus, preserving linear properties embedded within the original data are used to distinguish various sources and types of VPV. Differences in mutual information and sample entropy of VPV between original and surrogate data sets reflect nonlinear deterministic properties of the original data set. We have applied these analytic techniques to assess breathing pattern before and after vagotomy, cerebral ischemia, and lung injury. Deterministic variability decreased following each of these interventions. Finally, our approach can be applied to rhythmic biological signals.

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Acknowledgments

This research has been generously supported by NIH. HL-087377, NS069220 and VA Research Service I01BX000873.

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Authors and Affiliations

  1. Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH, 44106-1714, USA

    Thomas E. Dick Ph.D.

  2. Department of Neurosciences, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106, USA

    Rishi R. Dhingra B.S.

  3. Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University Hospital of Cleveland, 10900 Euclid Avenue, Cleveland, OH, 44106, USA

    Yee-Hsee Hsieh Ph.D.

  4. Department of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106, USA

    Mikkel Fishman B.S.

  5. Department of Electrical Engineering and Computer Science, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106, USA

    Farhad Kaffashi Ph.D. & Kenneth A. Loparo B.S., M.S., Ph.D.

  6. Division of Neonatology, Department of Pediatrics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106, USA

    Christopher G. Wilson Ph.D.

  7. Louis Stokes Cleveland VA Medical Center, Cleveland, OH, USA

    Frank J. Jacono M.D.

  8. University Hospitals Case Medical Center, 11100 Euclid Avenue, Wearn 622, Cleveland, OH, 44106, USA

    Frank J. Jacono M.D.

  9. Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Case Western Reserve University School of Medicine, Cleveland, OH, USA

    Frank J. Jacono M.D.

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  1. Thomas E. Dick Ph.D.
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  2. Rishi R. Dhingra B.S.
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  3. Yee-Hsee Hsieh Ph.D.
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  4. Mikkel Fishman B.S.
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  5. Farhad Kaffashi Ph.D.
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  6. Kenneth A. Loparo B.S., M.S., Ph.D.
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  7. Christopher G. Wilson Ph.D.
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  8. Frank J. Jacono M.D.
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Correspondence to Thomas E. Dick Ph.D. .

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Editors and Affiliations

  1. University of Pittsburgh Inflammation and Regenerative Modeling, Pittsburgh, Pennsylvania, USA

    Yoram Vodovotz

  2. University of Chicago Medical Center MC 5094, Chicago, Illinois, USA

    Gary An

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Dick, T.E. et al. (2013). Analysis of Ventilatory Pattern Variability. In: Vodovotz, Y., An, G. (eds) Complex Systems and Computational Biology Approaches to Acute Inflammation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8008-2_5

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