Signal Processing Methodology to Study the Cutaneous Vasodilator Response to a Local External Pressure Application Detected by Laser Doppler Flowmetry

Abstract

The existence of a cutaneous pressure-induced vasodilation (PIV) has recently been reported. This paper proposes a signal processing methodology to improve PIV knowledge. Temporal variations of laser Doppler signals rhythmic activities are first analyzed on anesthetized rats. The results lead to a method that provides a better PIV understanding.

Laser Doppler perfusion monitoring and imaging: novel approaches

“…Therefore, in order to have a precise knowledge of these activities at rest and during the application of a local and progressive pressure, on healthy and type 1 diabetic subjects, a study analysed LDF signals recorded at rest and during the application of a progressive pressure, on six diabetic patients with type 1 diabetes mellitus and without respiratory or cardiac failure, neuropathy of nondiabetic origin, peripheral vascular disease, psychological disorder or tremor, and on six age-matched non-diabetic control subjects [26]. Based on other studies [19,25,28], the scalograms of each signal were then studied between 0.0095 and 0.145 Hz, in order to obtain the three characteristic frequencies corresponding to the myogenic, neurogenic, and endothelial related metabolic activities: intervals 0.052-0.145, 0.021-0.052, 0.0095-0.021 Hz, respectively [26]. Quantitative measures were then calculated to make comparisons between sets of recordings: the energy of the time-frequency representation on a given frequency band [25,26], and the relative energy of the time-frequency representation on a frequency band [26].…”

Time and Spatial Invariance of Impedance Signals in Limbs of Healthy Subjects by Time–Frequency Analysis

“…Time and spatial invariance means that, for each characteristic frequency band of the signal, no statistical difference is found for the energy between the two different time intervals, nor between the site analyzed. 2,3,[9][10][11] To study time and spatial variations, it is therefore necessary to analyze the spectrum of impedance signals. However, impedance signals are weakly stationary, i.e., the characteristic frequencies of the signals slightly change continuously.…”

“…The scalogram has been chosen for this study because it has already proven to be very efficient for physiological signals. 9,10 In order to apply the wavelet transform on the impedance signal, it is necessary to choose a mother wavelet W(t), which will allow a wavelet family to be built by dilatation and translation. This wavelet family is an orthogonal base of the impedance signal.…”

“…For that purpose, the energy of the time frequency representation on a given frequency band was computed. 9 The results are denoted as Eventilation, Eheart and represent the energy of the TFR on the intervals 0.2-0.6 and 0.6-1.6 Hz, respectively. Moreover, in order to evaluate how the distribution of the energy among the two bands changes, we introduced the relative energy of the TRF on a frequency band.…”

“…Moreover, in order to evaluate how the distribution of the energy among the two bands changes, we introduced the relative energy of the TRF on a frequency band. 9 They are denoted as …”