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The purpose of this paper is to present wavelet-based noise removal (WBNR) techniques to remove noise from biomechanical acceleration signals obtained from numerical differentiation of displacement data. Manual and semiautomatic methods were used to determine thresholds for both orthogonal and biorthogonal filters. This study also compares the performance of WBNR approaches with four automatic conventional noise removal techniques used in biomechanics. The conclusion of this work is that WBNR techniques are very effective in removing noise from differentiated signals with sharp transients while leaving these transients intact. For biomechanical signals with certain characteristics, WBNR techniques perform better than conventional methods, as indicated by quantitative merit measures.

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Investigations into the changes that occur in microvasculature following the surgical procedure called delay have brought about the need for a computer system capable of quantifying the morphological features of a full microvascular network in terms of average vessel length, diameter, and tortuosity. Both the formulaic conventions that have been developed to measure these quantities as well as their implementation in the form of a HP-9000/UNIX based computer software system that we developed specifically for this purpose are discussed. Reliability studies performed using the final system to measure the microcirculatory network of a mouse latissmus dorsi muscle (LDM) showed 95% confidence intervals within 5% of means and coefficients of variability within 7% of means for all quantities measured in large (150-300 microns), medium (50-150 microns), and small (< 50 microns) diameter vessels. These variations were significantly smaller than the changes that were observed in a preliminary study comparing these microvascular network parameters before and after delay in the hairless mouse LDM, showing the proposed quantification methods to be well suited to the study of the microvascular changes following delay. It is hoped that the formulaic conventions, implementation process and reliability data will provide a useful comparison for other researchers interested in measuring similar features of microcirculatory networks.

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