Multiscale, multidomain analysis of microvascular flow dynamics.

To date, time- and frequency-domain metrics of signals acquired through laser Doppler fluximetry have been unable to provide consistent and robust measures of the changes that occur in the microcirculation in healthy individuals at rest or in response to a provocation, or in patient cohorts. Recent studies have shown that in many disease states, such as metabolic and cardiovascular disease, there appears to be a reduction in the adaptive capabilities of the microvascular network and a consequent reduction in physiological information content. Here, we introduce non-linear measures for assessing the information content of fluximetry signals and demonstrate how they can yield deeper understanding of network behaviour. In addition, we show how these methods may be adapted to accommodate the multiple time scales modulating blood flow and how they can be used in combination with time- and frequency-domain metrics to discriminate more effectively between the different mechanistic influences on network properties.