An adequate delivery of blood flow through a vascular network, commensurate with the metabolic demands of the tissue, is dependent on neural, humoral and local vaso-mechanisms that determine vascular tone and thus temporal and spatial flow patterns within the microvascular network. As alteration or attenuation of these flow patterns may be a contributor to disease risk, quantitative in vivo information on the temporal behaviour and spatial distribution is necessary to the understanding of network functionality and adaptivity with stressors or disease. Time and frequency domain analysis of Laser Doppler (LD) flowmetry signals has been extensively used to describe and characterise microvascular flows. Spectral analysis of the frequency components of LD signals has been shown to reflect the influence of the spontaneous, rhythmic oscillations of both local (endothelial, neurogenic and myogenic) and systemic origin. Variation in amplitude and spectral content have been associated with microvascular function decline in metabolic and CVD1. However, time and frequency domain analysis alone have proved insufficient for the consistent interpretation of microvascular function. Recently, methods to assess regularity and randomness, have been applied to LD signals. Chaotic network attractor analysis has shown a decline in adaptability of network flow in rodent models of metabolic and CVD2 and Lempel-Ziv (LZ) microvascular perfusion complexity reduced in a primate model of diabetes3. In previous work, we have shown that an altered spatial heterogeneity and temporal stability of network perfusion is associated with a decrease in both LZ complexity and sample entropy under differing haemodynamic states in healthy humans. Complexity and sample entropy were dependent on the time-scale of the perfusion measurement4. Time, frequency and complexity domain analysis of microvascular blood flow can provide robust parameters that provide a better understanding of the relationship between microvascular perfusion and CVD risk and account, to some degree, for the temporal scale of their origin in terms of the local and systemic physiological activity. The synchronicity of rhythms in the modulators of skin blood flux contributes to the complexity of microvascular blood flow and this reduces with CVD risk as flow becomes more homogenous and predictable. These multiple domain analyses and findings provide a platform from which to investigate microvascular impairment in the skin.