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Time–Frequency Approaches for the Detection of Interactions and Temporal Properties in Renal Autoregulation

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Abstract

We compare the influence of time–frequency methods on analysis of time-varying renal autoregulation properties. Particularly, we examine if detection probabilities are similar for amplitude and frequency modulation for a modulated simulation signal among five time–frequency approaches, and if time-varying changes in system gain are detected using four approaches for estimating time-varying transfer functions. Detection of amplitude and frequency modulation varied among methods and was dependent upon background noise added to the simulated data. Three non-parametric time–frequency methods accurately detected modulation at low frequencies across noise levels but not high frequencies; while the converse was true for a fourth, and a fifth non-parametric approach was not capable of modulation detection. When applied to estimation of time-varying transfer functions, the parametric approach provided the most accurate estimations of system gain changes, detecting a 1 dB step increase. Application of the appropriate methods to laser Doppler recordings of cortical blood flow and arterial pressure data in anesthetized rats reaffirm the presence of time-varying dynamics in renal autoregulation. An increase in the peak system gain and detection of amplitude modulation of the Myogenic mechanism both occurred after inhibition of nitric oxide synthase, suggesting a connection between the operation of underlying regulators and system performance.

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Acknowledgments

This work was supported by Canadian Institutes of Health Research Grant MOP-102694 to WAC, BB, and KHC. CGS was supported by an American Heart Association Predoctoral Fellowship.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA, USA

    Christopher G. Scully & Ki H. Chon

  2. Departments of Anesthesiology and Medicine, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, USA

    Kin L. Siu

  3. Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, BC, Canada

    William A. Cupples

  4. Departments of Medicine and Physiology, University of Alberta, Edmonton, AB, Canada

    Branko Braam

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  1. Christopher G. Scully
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  2. Kin L. Siu
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  5. Ki H. Chon
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Correspondence to Ki H. Chon.

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Associate Editor Nathalie Virag oversaw the review of this article.

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Scully, C.G., Siu, K.L., Cupples, W.A. et al. Time–Frequency Approaches for the Detection of Interactions and Temporal Properties in Renal Autoregulation. Ann Biomed Eng 41, 172–184 (2013). https://doi.org/10.1007/s10439-012-0625-1

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  • DOI: https://doi.org/10.1007/s10439-012-0625-1

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