Splinting or surgery for carpal tunnel syndrome? Design of a randomized controlled trial [ISRCTN18853827]

BACKGROUND: Carpal tunnel syndrome is a common disorder, which can be treated with surgery or conservative options. However, there is insufficient evidence and no consensus among physicians with regard to the preferred treatment for carpal tunnel syndrome. Therefore, a randomized controlled trial is conducted to compare the short- and long-term efficacy of surgery and splinting in patients with carpal tunnel syndrome. An attempt is also made to avoid the (methodological) limitations encountered in earlier trials on the efficacy of various treatment options for carpal tunnel syndrome. METHODS: Patients of 18 years and older, with clinically and electrophysiologically confirmed idiopathic carpal tunnel syndrome, are recruited by neurologists in 13 hospitals. Patients included in the study are randomly allocated to either open carpal tunnel release or wrist splinting during the night for at least 6 weeks. The primary outcomes are general improvement, waking up at night and severity of symptoms (main complaint, night and daytime pain, paraesthesia and hypoesthesia). Outcomes are assessed up to 18 months after randomization

A consistent full-field integrated DIC framework for HR-EBSD

\u3cp\u3eA general, transparent, finite-strain Integrated Digital Image Correlation (IDIC) framework for high angular resolution EBSD (HR-EBSD) is proposed, and implemented through a rigorous derivation of the optimization scheme starting from the fundamental brightness conservation equation in combination with a clear geometric model of the Electron BackScatter Pattern (EBSP) formation. This results in a direct one-step correlation of the full field-of-view of EBSPs, which is validated here on dynamically simulated patterns. Strain and rotation component errors are, on average, (well) below 10\u3csup\u3e−5\u3c/sup\u3e for small (E\u3csub\u3eeq\u3c/sub\u3e=0.05%) and medium (E\u3csub\u3eeq\u3c/sub\u3e=0.2%) strain, and below 3×10\u3csup\u3e−5\u3c/sup\u3e for large strain (E\u3csub\u3eeq\u3c/sub\u3e=1%), all for large rotations up to 10° and 2% image noise. High robustness against poor initial guesses (1° misorientation and zero strain) and typical convergence in 5 iterations is consistently observed for, respectively, image noise up to 20% and 5%. This high accuracy and robustness rivals, when comparing validation on dynamically simulated patterns, the most accurate HR-EBSD algorithms currently available which combine sophisticated filtering and remapping strategies with an indirect two-step correlation approach of local subset ROIs. The proposed general IDIC/HR-EBSD framework lays the foundation for future extensions towards more accurate EBSP formation models or even absolute HR-EBSD.\u3c/p\u3

Demonstrating the potential of accurate absolute cross-grain stress and orientation correlation using electron backscatter diffraction

\u3cp\u3eWe report a first exploration of High-angular-Resolution Electron Backscatter Diffraction, without using simulated Electron Backscatter Diffraction patterns as a reference, for absolute stress and orientation measurements in polycrystalline materials. By co-correlating the pattern center and fully exploiting crystal symmetry and plane-stress, simultaneous correlation of all overlapping regions of interest in multiple direct-electron-detector, energy-filtered Electron Backscatter Diffraction patterns is achieved. The potential for highly accurate measurement of absolute stress, crystal orientation and pattern center is demonstrated on a virtual polycrystalline case-study, showing errors respectively below 20 MPa (or 10\u3csup\u3e−4\u3c/sup\u3e in strain), 7 × 10\u3csup\u3e−5\u3c/sup\u3e rad and 0.06 pixels.\u3c/p\u3

Mechanical shape correlation:a novel integrated digital image correlation approach

\u3cp\u3eMechanical Shape Correlation (MSC) is a novel integrated digital image correlation technique, used to determine the optimal set of constitutive parameters to describe the experimentally observed mechanical behavior of a test specimen, based on digital images taken during the experiment. In contrast to regular digital image correlation techniques, where grayscale speckle patterns are correlated, the images used in MSC are projections of the sample contour. This enables the analysis of experiments for which this was previously not possible, because of restrictions due to the speckle pattern. For example, analysis becomes impossible if parts of the specimen move or rotate out of view as a result of complex and three-dimensional deformations and if the speckle pattern degrades due to large deformations. When correlating on the sample outline, these problems are overcome. However, it is necessary that the outline is large with respect to the structure volume and that its shape changes significantly upon deformation, to ensure sufficient sensitivity of the images to the model parameters. Virtual experiments concerning stretchable electronic interconnects, which because of their slender wire-like structure satisfy the conditions for MSC, are executed and yield accurate results in the objective model parameters. This is a promising result for the use of the MSC method for tests with stretchable electronics and other (micromechanical) experiments in general.\u3c/p\u3

Mechanical shape correlation: a novel integrated digital image correlation approach

Mechanical Shape Correlation (MSC) is a novel Integrated Digital Image Correlation (IDIC) based technique used for parameter identification. Digital images taken during an experiment are correlated and coupled to a Finite Element model of the specimen, in order to find the correct parameters in this numerical model. In contrast to regular IDIC techniques, where the images consist of a grayscale speckle pattern applied to the sample, in MSC the images are projections based on the contour lines of the test specimen only. This makes the technique suitable in cases where IDIC cannot be used, e.g., when large deformations and rotations cause parts of the sample to rotate in or out-of-view, or when the speckle pattern degrades due to large or complex deformations, or when application of the pattern is difficult because of small or large specimen dimensions. The method targets problems for which the outline of the specimen is large with respect to the volume of the structure and changes significantly upon deformation. The technique is here applied to virtual experiments with stretchable electronic interconnects, for identification of both elastic and plastic properties. Furthermore, attention is paid to the influence of algorithmic choices and experimental issues. The method reveals good convergence and adequate initial guess robustness. The results are promising and indicate that the method can be used in cases of either large, complex or three-dimensional displacements and rotations on any scale