Publications by authors named "Leopoldo Paolucci"

The objective of this study was to test a composite of polyester resin and fiberglass in the form of an intramedullary nail for osteosynthesis of femoral fractures in calves. The methodology was established based on a previous study that used a bovine femur finite element model to simulate fractures, which were then stabilized by the same nails as proposed in this study. General anesthesia was induced in six calves followed by fracture creation an oblique incision in the middle third of the femoral diaphysis, and osteosynthesis was immediately performed by retrograde insertion of the composite nail.

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This case study examined the association between 50 m freestyle and speed curve parameters of a world-class Paralympic swimmer and analysed the changes in speed curves and their frequency components across her performance levels. From 2018 to 2021, a visually impaired female swimmer (26.59 s in 50 m freestyle, S12 class) underwent 22 tests to obtain instantaneous speed synchronised with video recording.

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Background: To investigate the effect of different fixation strategies of the intramedullary interlocking nail (IIN) on the mechanical behavior of a polymeric implant applied for femoral fracture fixation in calves, and to evaluate the performance of a glass fiber-reinforced polymer applied in a bovine femoral fracture reduction system, five Holstein male animals with a mean weight (±SD) of 62.8 ± 20.4 kg and aged 74 ± 15 were used to generate biomechanical parameters for this study.

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Lower extremity kinetic data during walking of 12 people with chronic poststroke were reanalyzed, using functional analysis of variance (FANOVA). To perform the FANOVA, the whole curve is represented by a mathematical function, which spans the whole gait cycle and avoids the need to identify isolated points, as required for traditional parametric analyses of variance (ANOVA). The power variables at the ankle, knee, and hip joints, in the sagittal plane, were compared between two conditions: With and without walking sticks at comfortable and fast speeds.

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The aim of this study was to present a new training algorithm using artificial neural networks called multi-objective least absolute shrinkage and selection operator (MOBJ-LASSO) applied to the classification of dynamic gait patterns. The movement pattern is identified by 20 characteristics from the three components of the ground reaction force which are used as input information for the neural networks in gender-specific gait classification. The classification performance between MOBJ-LASSO (97.

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