Correlation analysis of laser Doppler flowmetry signals: a potential non-invasive tool to assess microcirculatory changes in diabetes mellitus.

Measurement and analysis of microcirculation is vital in assessing local and systemic tissue health. Changes in microvascular perfusion if detected can provide information on the development of various related diseases. Laser Doppler blood flowmetry (LDF) provides a non-invasive real-time measurement of cutaneous blood perfusion. LDF signals possess fractal nature that represents the correlation in the successive signal elements. Changes in the correlation of flow and its associated parameters could be used as a tool in differentiating the ailments at different stages or assessing the treatment effectiveness of a particular ailment. Spectral domain analysis of LDF signals reveals five characteristic frequency peaks corresponding to local and central regulatory mechanisms of the human body, namely metabolic, neurogenic, myogenic, respiration, and heart rate. This paper investigates the changes in the fractal nature and constituent frequency bands of laser Doppler signals in diabetic and healthy control subjects acquired from the glabrous skin of the foot so as to provide an assessment of microcirculatory dynamics. As a pilot study, it was attempted on a set of healthy control and diabetic volunteers, and the obtained results indicate that fractal nature of LDF signals is less in diabetic subjects compared to the healthy control. The wavelet analysis carried out on the set of signals reveals the dynamics of blood flow which may have led to the difference in correlation results.