0000000000237802

AUTHOR

José M. Iñesta

0000-0001-6184-4694

Software tools for using a personal computer as a timer device to assess human kinematic performance: a case study.

Frequently, the assessment of the physical condition of a sportsman depends on the evaluation of different tests, based on biomechanical performance. The data acquisition in these tests is usually hand made, because its automatization is difficult. But when movements are constrained by means of their specific nature, simple tools can be used to achieve that data acquisition. In this paper, a simple and inexpensive system is described to make use of the timing capabilities of a personal computer (PC) to use it as a timer, with applications in biomechanics and sport training. The data acquisition method is based on a PC that, using a specific programming dealing with event timing, gets signal…

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Local symmetries of digital contours from their chain codes

In this work symmetry is evaluated as a numeric feature for each point of a contour, using only the positions of a local vicinity of points. A measurement is defined, named as Local Symmetric Deficiency (LSD), so that the lower this quantity is, the higher the symmetry will be in the local region considered. This approach is very simple and it is based on a suitable manipulation of the chain code of the curve. Its computational cost is very low and it has the advantages of a parallel algorithm, since values for LSD can be computed for each point independently.

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Geometric Properties of the 3D Spine Curve

Through a 3D reconstruction of the human back surface using structured light techniques, we study the properties of spine curve by means of a set of parameters related to measures commonly applied in medicine. In this way, descriptors for measuring the abnormalities in the projections of the front and sagittal planes can be computed. We build the spine curve in 3D and analyse the behaviour of the Frenet frame when along the curve the deformation processes in idiophatic scoliosis appear.

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Reliable polygonal approximations of imaged real objects through dominant point detection

Abstract The problem of dominant point detection is posed, taking into account what usually happens in practice. The algorithms found in the literature often prove their performance with laboratory contours, but the shapes in real images present noise, quantization, and high inter and intra-shape variability. These effects are analyzed and solutions to them are proposed. We will also focus on the conditions for an efficient (few points) and precise (low error) dominant point extraction that preserves the original shape. A measurement of the committed error (optimization error, E 0 ) that takes into account both aspects is defined for studying this feature.

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