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1.
Front Hum Neurosci ; 15: 741709, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-35095444

RESUMO

Motor Imagery (MI) reproduces cognitive operations associated with the actual motor preparation and execution. Postural recordings during MI reflect somatic motor commands targeting peripheral effectors involved in balance control. However, how these relate to the actual motor expertise and may vary along with the MI modality remains debated. In the present experiment, two groups of expert and non-expert gymnasts underwent stabilometric assessments while performing physically and mentally a balance skill. We implemented psychometric measures of MI ability, while stabilometric variables were calculated from the center of pressure (COP) oscillations. Psychometric evaluations revealed greater MI ability in experts, specifically for the visual modality. Experts exhibited reduced surface COP oscillations in the antero-posterior axis compared to non-experts during the balance skill (14.90%, 95% CI 34.48-4.68, p < 0.05). Experts further exhibited reduced length of COP displacement in the antero-posterior axis and as a function of the displacement area during visual and kinesthetic MI compared to the control condition (20.51%, 95% CI 0.99-40.03 and 21.85%, 95% CI 2.33-41.37, respectively, both p < 0.05). Predictive relationships were found between the stabilometric correlates of visual MI and physical practice of the balance skill, as well as between the stabilometric correlates of kinesthetic MI and the training experience in experts. Present results provide original stabilometric insights into the relationships between MI and expertise level. While data support the incomplete inhibition of postural commands during MI, whether postural responses during MI of various modalities mirror the level of motor expertise remains unclear.

2.
PLoS One ; 15(12): e0235024, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33264298

RESUMO

The objective of this work is to provide a mathematical analysis on how a Thoroughbred horse should regulate its speed over the course of a race to optimize performance. Because Thoroughbred horses are not capable of running the whole race at top speed, determining what pace to set and when to unleash the burst of speed is essential. Our model relies on mechanics, energetics (both aerobic and anaerobic) and motor control. It is a system of coupled ordinary differential equations on the velocity, the propulsive force and the anaerobic energy, that leads to an optimal control problem that we solve. In order to identify the parameters meaningful for Thoroughbred horses, we use velocity data on races in Chantilly (France) provided by France Galop, the French governing body of flat horse racing in France. Our numerical simulations of performance optimization then provide the optimal speed along the race, the oxygen uptake evolution in a race, as well as the energy or the propulsive force. It also predicts how the horse has to change its effort and velocity according to the topography (altitude and bending) of the track.


Assuntos
Cavalos/fisiologia , Corrida/fisiologia , Algoritmos , Altitude , Anaerobiose , Animais , Comportamento Competitivo , Consumo de Oxigênio , Condicionamento Físico Animal/fisiologia , Medicina Veterinária Esportiva/métodos
3.
Am J Physiol Heart Circ Physiol ; 319(4): H882-H892, 2020 10 01.
Artigo em Inglês | MEDLINE | ID: mdl-32822212

RESUMO

Diastolic dysfunction (DD) is a major component of heart failure with preserved ejection fraction (HFpEF). Accordingly, a profound understanding of the underlying biomechanical mechanisms involved in DD is needed to elucidate all aspects of HFpEF. In this study, we have developed a computational model of DD by leveraging the power of an advanced one-dimensional arterial network coupled to a four-chambered zero-dimensional cardiac model. The two main pathologies investigated were linked to the active relaxation of the myocardium and the passive stiffness of the left ventricular wall. These pathologies were quantified through two parameters for the biphasic delay of active relaxation, which simulate the early and late-phase relaxation delay, and one parameter for passive stiffness, which simulates the increased nonlinear stiffness of the ventricular wall. A parameter sensitivity analysis was conducted on each of the three parameters to investigate their effect in isolation. The three parameters were then concurrently adjusted to produce the three main phenotypes of DD. It was found that the impaired relaxation phenotype can be replicated by mainly manipulating the active relaxation, the pseudo-normal phenotype was replicated by manipulating both the active relaxation and passive stiffness, and, finally, the restricted phenotype was replicated by mainly changing the passive stiffness. This article presents a simple model producing a holistic and comprehensive replication of the main DD phenotypes and presents novel biomechanical insights on how key parameters defining the relaxation and stiffness properties of the myocardium affect the development and manifestation of DD.NEW & NOTEWORTHY This study uses a complete and validated computational model of the cardiovascular system to simulate the two main pathologies involved in diastolic dysfunction (DD), i.e., abnormal active relaxation and increased ventricular diastolic stiffness. The three phenotypes of DD were successfully replicated according to literature data. We elucidate the biomechanical effect of the relaxation pathologies involved and how these pathologies interact to create the various phenotypes of DD.


Assuntos
Simulação por Computador , Insuficiência Cardíaca/fisiopatologia , Modelos Cardiovasculares , Disfunção Ventricular Esquerda/fisiopatologia , Função Ventricular Esquerda , Fenômenos Biomecânicos , Diástole , Humanos , Fenótipo , Volume Sistólico , Pressão Ventricular
4.
Front Sports Act Living ; 2: 636428, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33554112

RESUMO

The distribution of energetic resources in world-class distance running is a key aspect of performance, with athletes relying on aerobic and anaerobic metabolism to greater extents during different parts of the race. The purpose of this study is to model 10,000 m championship performances to enable a deeper understanding of the factors affecting running speed and, given that more than half the race is run on curves, to establish the effect of the bends on performance. Because a limitation of time split data is that they are typically averaged over 100-m or 1,000-m segments, we simulate two 10,000 m runners' performances and thus get access to their instantaneous speed, propulsive force and anaerobic energy. The numerical simulations provide information on the factors that affect performance, and we precisely see the effect of parameters that influence race strategy, fatigue, and the ability to speed up and deal with bends. In particular, a lower anaerobic capacity leads to an inability to accelerate at the end of the race, and which can accrue because of a reliance on anaerobic energy to maintain pace in an athlete of inferior running economy. We also see that a runner with a worse running economy is less able to speed up on the straights and that, in general, the bends are run slower than the straights, most likely because bend running at the same pace would increase energy expenditure. Notwithstanding a recommendation for adopting the accepted practices of improving aerobic and anaerobic metabolism through appropriate training methods, coaches are advised to note that athletes who avoid mid-race surges can improve their endspurt, which are the differentiating element in closely contested championship races.

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