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Venous ulcers are deep wounds that are located predominantly on the lower leg. They are prone to infection and once healed have a high probability of recurrence. Currently, there are no effective measures to predict and prevent venous ulcers from formation. Hence, the goal of this work was to develop a Windkessel-based model that can be used to identify hemodynamic parameters that change between healthy individuals and those with wounds. Once identified, these parameters have the potential to be used as indicators of when internal conditions change, putting the patient at higher risk for wound formation. In order to achieve this goal, blood flow responses in lower legs were measured experimentally by a laser Doppler perfusion monitor (LDPM) and simulated with a modeling approach. A circuit model was developed on the basis of the Windkessel theory. The hemodynamic parameters were extracted for three groups: legs with ulcers ("wounded"), legs without ulcers but from ulcer patients ("nonwounded"), and legs without vascular disease ("healthy"). The model was executed by two independent operators, and both operators reported significant differences between wounded and healthy legs in localized vascular resistance and compliance. The model successfully replicated the experimental blood flow profile. The global and local vascular resistances and compliance parameters rendered quantifiable differences between a population with venous ulcers and healthy individuals. This work supports that the Windkessel modeling approach has the potential to determine patient specific parameters that can be used to identify when conditions change making venous ulcer formation more likely. [ABSTRACT FROM AUTHOR]

Millions of people have reduced hand function; this loss of function can be due to injury, disease, or aging. Loss of hand function is identified as reduced motion abilities in the fingers or a decrease in the ability of the fingers to generate force. Unfortunately, there are limited data available regarding each finger's ability to produce force and how those force characteristics vary with changes in finger posture. To relate motion and force abilities of the fingers, first, an approach to measure and map them together is needed. The goal of this work was to develop and demonstrate a method to quantify the force abilities of the fingers and map these forces to the kinematic space associated with each finger. Using motion capture and multiaxis load cells, finger forces were quantified at different positions over their ranges of motion. These two sets of data were then converted to the same coordinate space and mapped together. Further, the data were normalized for the index finger and mapped as a population space model. The ability to quantify motion and force data for each finger and map them together will provide an improved understanding of the effects of treatments and rehabilitation, identifying functional loss due to injury or disease, and device design. [ABSTRACT FROM AUTHOR]