Laser Doppler et microcirculation

à Paris (France) le 23/09/2009Journée du club "Société Francophone pour l'Informatique et le Monitorage en Anesthésie Réanimation" (SFIMAR) du congrès de la Société Française d'Anesthésie Réanimation (SFAR

Multifractal analysis of central (electrocardiography) and peripheral (laser Doppler flowmetry) cardiovascular time series from healthy human subjects

Analysis of the cardiovascular system (CVS) activity is important for several purposes, including better understanding of heart physiology, diagnosis and forecast of cardiac events. The central CVS, through the study of heart rate variability (HRV), has been shown to exhibit multifractal properties, possibly evolving with physiologic or pathologic states of the organism. An additional viewpoint on the CVS is provided at the peripheral level by laser Doppler flowmetry (LDF), which enables local blood perfusion monitoring. We report here for the first time a multifractal analysis of LDF signals through the computation of their multifractal spectra. The method for estimation of the multifractal spectra, based on the box method, is first described and tested on a priori known synthetic multifractal signals, before application to LDF data. Moreover, simultaneous recordings of both central HRV and peripheral LDF signals, and corresponding multifractal analyses, are performed to confront their properties. With the scales chosen on the partition functions to compute Renyi exponents, LDF signals appear to have broader multifractal spectra compared to HRV. Various conditions for LDF acquisitions are tested showing larger multifractal spectra for signals recorded on fingers than on forearms. The results uncover complex interactions at central and peripheral CVS levels

Multifractal analysis of heart rate variability and laser Doppler flowmetry fluctuations:comparison of results from different numerical methods

To contribute to the understanding of the complex dynamics in the cardiovascular system (CVS), the central CVS has previously been analyzed through multifractal analyses of heart rate variability (HRV) signals that were shown to bring useful contributions. Similar approaches for the peripheral CVS through the analysis of laser Doppler flowmetry (LDF) signals are comparatively very recent. In this direction, we propose here a study of the peripheral CVS through a multifractal analysis of LDF fluctuations, together with a comparison of the results with those obtained on HRV fluctuations simultaneously recorded. To perform these investigations concerning the biophysics of the CVS, first we have to address the problem of selecting a suitable methodology for multifractal analysis, allowing us to extract meaningful interpretations on biophysical signals. For this purpose, we test four existing methodologies of multifractal analysis. We also present a comparison of their applicability and interpretability when implemented on both simulated multifractal signals of reference and on experimental signals from the CVS. One essential outcome of the study is that the multifractal properties observed from both the LDF fluctuations (peripheral CVS) and the HRV fluctuations (central CVS) appear very close and similar over the studied range of scales relevant to physiology

Multiscale entropy of laser Doppler flowmetry signals in healthy human subjects

Purpose: The cardiovascular system (CVS) regulation can be studied from acentral viewpoint, through heart rate variability (HRV) data, and from a peripheral viewpoint, through laser Doppler flowmetry (LDF) signals. Both the central and peripheral CVSs are regulated by several interacting mechanisms, each having its own temporal scale. The central CVS has been the subject of many multiscale studies. By contrast, these studies at the level of the peripheral CVS are very recent. Among the multiscale studies performed on the central CVS data, multiscale entropy has been proven to give interesting physiological information for diagnostic purposes. However, no multiscale entropyanalysis has been performed on LDF signals. The authors’ goal is therefore to propose a first multiscale entropy study of LDF data recorded in healthy subjects. Methods: The LDF signals recorded in the forearm of seven healthy subjects are processed. Their period sampling is T = 50 ms , and coarse-graining scales from T to 23 T are studied. Also, for validation, the algorithm is first tested on synthetic signals of known theoretical multiscale entropy. Results: The results reveal nonmonotonic evolution of the multiscale entropy of LDF signals, with a maximum at small scales around 7 T and a minimum at longer scales around 18 T , singling out in this way two distinctive scales where the LDF signals undergo specific changes from high to low complexity. This also marks a strong contrast with the HRV signals that usually display a monotonic increase in the evolution of the multiscale entropy. Conclusions: Multiscale entropy of LDF signals in healthy subjects shows variation with scales. Moreover, as the variation pattern observed appears similar for all the tested signals, multiscale entropy could potentially be a useful stationary signature for LDF signals, which otherwise are probe-position and subject dependent. Further work could now be conducted to evaluate possible diagnostic purposes of the multiscale entropy of LDF signals

A new method to determine arterial distensibility in small arteries

Several methods allow to measure arterial distensibilty. One of them consists in estimating the direct distensibility (D) from diameter and distending blood pressure. Herein, we propose a new method to assess the distensibility in small arteries which is based on spectral analysis of time motion mode ultrasound images of radial arteries. A Fourier transform was performed on intensity of upper and lower walls. Spectral amplitude at heart frequency from both wall spectra was estimated and summed (SumAmp). SumAmp was then compared with direct distensibility. A significant correlation was found between SumAmp and D (r = 0.7, p = 0.02)

Multifractal spectra of laser Doppler flowmetry signals in healthy and sleep apnea syndrome subjects

Laser Doppler flowmetry (LDF) signals give a peripheral view of the cardiovascular system. To better understand the possible modifications brought by sleep apnea syndrome (SAS) in LDF signals, we herein propose to analyze the complexity of such signals in obstructive SAS subjects, and to compare the results with those obtained in healthy subjects. SAS is a pathology that leads to a drop in the parasympathetic tone associated with an increase in the sympathetic tone in awakens SAS patients. Nine men with obstructive SAS and nine healthy men participated awaken in our study and LDF signals were recorded in the forearm. In our work, complexity of LDF signals is analyzed through the computation and analysis of their multifractal spectra. The multifractal spectra are estimated by first estimating the discrete partition function of the signals, then by determining their Renyi exponents with a linear regression, and finally by computing their Legendre transform. The results show that, at rest, obstructive SAS has no or little impact on the multifractal spectra of LDF signals recorded in the forearm. This study shows that the physiological modifications brought by obstructive SAS do not modify the complexity of LDF signals when recorded in the forearm