12 research outputs found

    A MISSING LINK FOR AN EFFECTIVE REHABILITATION

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    Sensorless Control of Surface-Mount Permanent-Magnet Synchronous Motors Based on a Nonlinear Observer

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    International audienceA nonlinear observer for surface-mount permanent-magnet synchronous motors (SPMSMs) was recently proposed by Ortega et al.(LSS, Gif-sur-Yvette Cedex, France, LSS Internal Rep., Jan. 2009). The nonlinear observer generates the position estimate hat(theta) via the estimates of sin theta and cos theta. In contrast to Luenberger-type observers, it does not require speed information, thus eliminating the complexity associated with speed estimation errors. Further, it is simple to implement. In this study, the nonlinear observer performance is verified experimentally. To obtain speed estimates from the position information, a proportional-integral (PI) tracking controller speed estimator was utilized. The results are good with and without loads, above 10 r/min

    A STUDY ON THE CORRELATION BETWEEN THE FOOT FEATURES AND GAIT CHARACTERISTICS DURING OVER-GROUND WALKING

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    We analysed the correlation between the foot features such as foot length, foot width, the height and angles of foot arch curves and gait spatiotemporal parameters. To measure the structure of the foot, we measured the height and structural variation of medial longitudinal arch(MLA) and lateral longitudinal arch(LLA) in various conditions using a �� Scanning stage�� consisting of a single depth camera and four uni-axial force sensors. The gait spatiotemporal parameters were obtained by a motion capture system from the seventeen subjects. All subjects were instructed to walk at a regular pace, and spatiotemporal gait parameters of ten strides in the middle of the walkway were measured. As a result, it has been shown that the height angle of MLA is significantly correlated with gait temporal parameters while the LLA is significantly related to gait spatial parameters

    A MACHINE-LEARNING-BASED GAIT ESTIMATION FROM THE FOOT ARCH PARAMETERS MEASURED BY A FOOT SCANNING SYSTEM

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    The purpose of this study is to develop a machine-learning-based regressor to estimate the gait-related parameters from the foot characteristics extracted by a foot scanning system. A fully-connected feed-forward neural network model was used to predict the gait parameters. The inputs of the model were the foot arch features and body anthropometric data, while the outputs of the model were the spatiotemporal gait parameters of the regular walking. The performance of the model was verified showing the accuracy of 95% or higher confirming the facts that foot features are dominant factors to estimate personalized gait patterns. In conclusion, the gait pattern can be easily assessed by measuring the foot depth-image from the foot scanner without using complex and expensive traditional methods if the data pools are significantly increased

    Effects of Short-Rest Interval Time on Resisted Sprint Performance and Sprint Mechanical Variables in Elite Youth Soccer Players

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    This study explored the impact of short rest intervals on resisted sprint training in elite youth soccer players, specifically targeting enhanced initial-phase explosive acceleration without altering sprint mechanics. Fifteen U19 soccer players participated in a randomized crossover design trial, executing two sprint conditions: RST2M (6 sprints of 20 m resisted sprints with 2 min rest intervals) and RST40S (6 sprints of 20 m resisted sprints with 40 s rest intervals), both under a load equivalent to 30% of sprint velocity decrement using a resistance device. To gauge neuromuscular fatigue, countermovement jumps were performed before and after each session, and the fatigue index along with sprint decrement percentage were calculated. Interestingly, the results indicated no significant differences in sprint performance or mechanical variables between RST2M and RST40S, suggesting that the duration of rest intervals did not affect the outcomes. Horizontal resistance appeared to mitigate compensatory patterns typically induced by fatigue in short rest periods, maintaining effective joint movement and hip extensor recruitment necessary for producing horizontal ground forces. These findings propose a novel training strategy that could simultaneously enhance sprint mechanics during initial accelerations and repeated sprint abilities for elite youth soccer players—a methodology not previously employe

    The Origin of Selective Adsorption of CO2 on Merlinoite Zeolites

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    Herein, we describe the CO2 adsorption behavior at 25‐75 °C and 0−1.0 bar of various alkali cation‐exchanged forms of merlinoite (framework type MER) zeolites with Si/Al = 2.3 and 3.8. The adsorption isotherms at 25 °C on the Na+ , K+ , Rb+ , and Cs+ forms of MER zeolite with Si/Al = 2.3 are characterized by a clear step, the CO2 pressure of which differs notably according to the type of their extraframework cations. Structural analysis shows that CO2 adsorption on the former three zeolites includes the relocation of gating cations with high site occupancy and the remarkable concomitant structural breathing. We define this unusual adsorption phenomenon as a cooperative cation gating‐breathing mechanism. The overall results suggest that the actual mechanism of selective CO2 adsorption on intermediate‐silica small‐pore zeolites can change from cation gating to cooperative cation gating‐breathing to breathing, depending on a combination of their topological and compositional (framework Al content and extraframework cation type and concentration) flexibilities.11Nsciescopu
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