Innovative non-invasive microvascular assessment

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A major challenge facing public health is the increased incidence and prevalence of cardio-metabolic and related diseases, e.g. metabolic syndrome, diabetes and obesity. Changes in the spontaneous oscillations observable in microvascular blood flow may precede other measures of autonomic dysfunction that occur in these diseases and could help in their early detection or treatment. Laser Doppler flowmetry (LDF), with a measurement volume of approximately 1mm3, has been extensively used to date to provide a non-invasive technique for investigating the motion of red blood cells and the assessment of microvascular function and possible disease state. However, this method provides only a relative index of blood perfusion and can lack precision and repeatability when measuring different skin sites. Laser speckle contrast imaging (LCSI) allows measurement from larger skin areas (approximately 7cm x 7cm) yielding spatial and temporal measurement of blood flow and is investigated in this project to assess if the technique can be used to provide improved diagnostic or quantitative descriptive capabilities.The primary research question is to determine if there are patterns in blood flow that correspond to known mechanisms of microvascular dysfunction in disease states and if these can be used as features to classify or stratify disease risk. In particular, the utility of the larger measurement area available in continuous LCSI will be investigated to test whether this can be used to overcome some of the limitations of LDF, including measurement site specificity.The operational and measurement characteristics of the LCSI will be evaluated and their influence on the measured data determined. Data from baseline signals (at rest) and response to challenges/stimuli (e.g. arterial occlusion, heating, cooling) in healthy and disease groups, (e.g. with or without diabetes (type 1 or 2)), will be evaluated in the time and frequency domain and compared with that achieved by LDF. The size and location of regions of interest in the LSCI field will be considered and techniques developed to aid or automate their selection. Information theoretic approaches to signal processing (Lempel-Ziv complexity, sample entropy and attractor reconstruction) will be developed and employed to provide features for classification schemes.The novel engineering content of this research derives from the development and use of information theoretic approaches to the digital signal processing and their adaptation to account for the multiple time-scales of the different processes modulating skin blood flow. The use of LSCI will also facilitate the novel use of spatiotemporal complexity analysis to elucidate further understanding of the system level behaviour of microvascular beds. Such approaches are of interest in many areas of bio-signal processing but have potential application in many other engineering fields such as health and condition monitoring, traffic flows and systems theory.Healthcare technologies themeClinical technologiesDigital signal processing