Wavelet analysis of laser Doppler microcirculatory signals: Current applications and limitations

Abstract

Laser Doppler flowmetry (LDF) has long been considered a gold standard for non-invasive assessment of skin microvascular function. Due to the laser Doppler (LD) microcirculatory signal’s complex biological and physiological context, using spectral analysis is advisable to extract as many of the signal’s properties as feasible. Spectral analysis can be performed using either a classical Fourier transform (FT) technique, which has the disadvantage of not being able to localize a signal in time, or wavelet analysis (WA), which provides both the time and frequency localization of the inspected signal. So far, WA of LD microcirculatory signals has revealed five characteristic frequency intervals, ranging from 0.005 to 2 Hz, each of which being related to a specific physiological influence modulating skin microcirculatory response, providing for a more thorough analysis of the signals measured in healthy and diseased individuals. Even though WA is a valuable tool for analyzing and evaluating LDF-measured microcirculatory signals, limitations remain, resulting in a lack of analytical standardization. As a more accurate assessment of human skin microcirculation may better enhance the prognosis of diseases marked by microvascular dysfunction, searching for improvements to the WA method is crucial from the clinical point of view. Accordingly, we have summarized and discussed WA application and its limitations when evaluating LD microcirculatory signals, and presented insight into possible future improvements. We adopted a novel strategy when presenting the findings of recent studies using WA by focusing on frequency intervals to contrast the findings of the various studies undertaken thus far and highlight their disparities.

Research progress and clinical application of laser Doppler blood flow measurement technology

“…Studies indicate that methods such as reducing the aperture of fiber-optic laser probes, keeping the probe close to and relatively still with the skin, using VCSEL chips to make integrated optoelectronic probes, avoiding the use of optical fibers, and employing wavelet analysis algorithms to filter out artifacts can significantly reduce the impact of motion artifacts on the accuracy of blood flow perfusion measurements. However, wavelet analysis has limitations, such as edge effects, when analyzing blood flow signals, requiring further research for resolution [60]. Additionally, using lasers with longer wavelengths, such as near-infrared, high-power pulse lasers with a peak power of 20mW, and a large sourceto-detector distance of 20-60mm, can significantly improve the tissue penetration depth and signal-to-noise ratio of LDF.…”

Cerebral Circulation and Brain Temperature during an Ultra-Short Session of Dry Immersion in Young Subjects

“…The data obtained indicate, in general, the stability of the cerebral blood flow during a DI session because most of LDF parameters did not change. Oscillations in the respiration dependent frequency range predominantly indicate the venous blood flow because the respiratory system is one of the major drivers for venous return to the heart [ 38 , 39 ]. The respiratory component of LDF is believed to increase during venous stasis [ 34 , 35 ].…”

The Physiology of Thermoregulation in Exercise

“…2), various laser Doppler imaging techniques (55,56) or ultrasound Doppler flowmetry (UDF) (57), and have been considered to be a more reliable measure of SkBF than plethysmography (58,59). To obtain a better insight into the particular physiological mechanism behind it, different approaches and algorithms are being developed for the spectral decomposition of the LDF signal (60). Interestingly, glabrous and non-glabrous parts of the skin behave differently during exercise and its recovery (45, 57, 61) (Fig.…”