Wavelet analysis of autonomic outflow of normal subjects on head-up tilt, cold pressor test, Valsalva manoeuvre and deep breathing

Authors

  • J. L. Ducla-Soares,

    1. Institute of Physiology, Faculty of Medicine of Lisbon, Avenue Professor Egas Moniz, 1649-028 Lisbon, Portugal, Unit of Autonomic Nervous System, Instituto de Medicina Molecular, Lisbon, Portugal
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  • M. Santos-Bento,

    1. Institute of Physiology, Faculty of Medicine of Lisbon, Avenue Professor Egas Moniz, 1649-028 Lisbon, Portugal, Unit of Autonomic Nervous System, Instituto de Medicina Molecular, Lisbon, Portugal
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  • S. Laranjo,

    1. Institute of Physiology, Faculty of Medicine of Lisbon, Avenue Professor Egas Moniz, 1649-028 Lisbon, Portugal, Unit of Autonomic Nervous System, Instituto de Medicina Molecular, Lisbon, Portugal
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  • A. Andrade,

    1. Institute of Biophysics & Biomedical Engineering, Faculty of Sciences of Lisbon, Campo Grande, 1749-016 Lisbon, Portugal
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  • E. Ducla-Soares,

    1. Institute of Biophysics & Biomedical Engineering, Faculty of Sciences of Lisbon, Campo Grande, 1749-016 Lisbon, Portugal
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  • J. P. Boto,

    1. CMAF, Lisbon, Portugal
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  • L. Silva-Carvalho,

    1. Institute of Physiology, Faculty of Medicine of Lisbon, Avenue Professor Egas Moniz, 1649-028 Lisbon, Portugal, Unit of Autonomic Nervous System, Instituto de Medicina Molecular, Lisbon, Portugal
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  • I. Rocha

    1. Institute of Physiology, Faculty of Medicine of Lisbon, Avenue Professor Egas Moniz, 1649-028 Lisbon, Portugal, Unit of Autonomic Nervous System, Instituto de Medicina Molecular, Lisbon, Portugal
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Corresponding author I. Rocha: Instituto de Fisiologia, Faculdade de Medicina de Lisboa, Avenue Professor Egas Moniz, 1649-028 Lisbon, Portugal. Email: isabelrocha@fm.ul.pt

Abstract

Non-invasive autonomic evaluation has used fast Fourier transform (FFT) to assign a range of low (LF) and high frequencies (HF) as markers of sympathetic and parasympathetic influences, respectively. However, FFT cannot be applied to brief transient phenomena, such as those observed on performing autonomic tests where the acute changes of cardiovascular signals (blood pressure and heart rate) that represent the first and most important stage of the autonomic performance towards a new state of equilibrium occur. Wavelet analysis has been proposed as a method to overcome and complement information taken exclusively in the frequency domain. With discrete wavelet transform (DWT), a time–frequency analysis can be done, allowing the visualization in time of the contribution of LF and HF to the observed changes of a particular signal. In this study, we evaluate with wavelets the acute changes in R–R intervals and systolic blood pressure that are observed in normal subjects during four classical autonomic tests: head-up tilt (HUT), cold pressor test (CPT), deep breathing (DB) and Valsalva manoeuvre (VM). Continuous monitoring of ECG and blood presure was performed. Also LF, HF and LF/HF were calculated. Consistent with previous interpretations, data showed an increase of sympathetic activity in HUT, CPT and VM. On DB, results reflected an increase in parasympathetic activity and frequencies. In conclusion, when compared with FFT, wavelet analysis allows the evaluation of autonomic variability during short and non-stationary periods of time and may constitute a useful advance in the assessment of autonomic function in both physiological and pathological conditions.

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