The Valsalva maneuver revisited by wavelets.

The Valsalva maneuver is an autonomic test that evokes short sharp cardiovascular fluctuations mediated by the autonomic nervous system. Numerous spectral analysis methods have been proposed to analyze biological signals. When applied to heart rate (HR) variability, two major bands related to autonomic influence have been defined: LF (mainly sympathetic) and HF (parasympathetic). However, conventional spectral approaches are based on the assumption of stationarity, and most require at least five minutes of recording. These two requirements cannot be fulfilled when analysis of dynamic processes such as the regulatory action of the autonomic nervous system is required. Wavelet transform is a mathematical tool that, by determining the temporal localization of the changes, the frequencies involved and their contribution to the entire signal, overcomes the limitations imposed by conventional methods. In the present work, we use wavelets to evaluate autonomic influence through the LF and HF band powers on acute changes in systolic blood pressure (sBP) and RR intervals (RRI) during the Valsalva maneuver. Eighteen healthy volunteers performed the maneuver by blowing, after a deep inspiration and with a closed glottis, against a pressure of 40 mmHg for 15 seconds. Data were analyzed in three different periods: 1) the last minute just prior to the test (CTR); 2) the 15 seconds of the Valsalva maneuver (VM); 3) during the next 35 seconds after the maneuver (aVM). We observed that LF power increased in sBP and RRI in both VM and ower only increased after Valsalva. The data showed a marked increase in sympathetic activity during and after the maneuver and an increase in parasympathetic outflow after aVM. In conclusion, the ability of wavelets to analyze short non-stationary signals makes wavelet transform a promising tool to evaluate physiological and pathological autonomic conditions.

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

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.

Intraocular pressure variability in the anesthetized rat: a spectral analysis.

PURPOSE: Intraocular pressure (IOP) is a measure of the balance between the inflow and outflow of the aqueous humor, being in close relationship with the venous ocular blood flow. But the influence of the autonomic nervous system upon this variable is not well understood. One of the most frequently used mathematical tools for the evaluation of the autonomic nervous system in the frequency domain is the fast Fourier algorithm (FFT) applied to the analysis of heart rate (HR) and arterial blood pressure (BP). For these variables, a power spectrum has been built showing the major bands: very low frequency, lower frequency, and higher frequency (HF). The range of these bands depends on the animal species. In this study, the authors used FFT to analyze the variability of IOP in anesthetized rats. METHODS: BP and electrocardiogram were acquired at 2 KHz in all animals before and following muscle blockade and artificial ventilation at the same frequency as the spontaneous ventilation. Also, in this last condition, IOP was recorded before and after the application of atropine in the eye. RESULTS: Results show three bands in the IOP spectrum, a similar profile to those observed in the HR and BP spectra, with HF band modified after atropine application DISCUSSION: The discussion calls attention to the influence of the autonomic nervous system on IOP and suggests the possibility of clinical application of this methodology on diagnosis and therapeutic efficacy.