ORCID Profile
0000-0002-4310-2942
Current Organisation
University of Western Australia
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Publisher: American Physical Society (APS)
Date: 07-12-2020
Publisher: SAGE Publications
Date: 16-09-2020
Abstract: Performing a motor task depends on the level of performance stabilization and movement control, and both aspects of motor behavior are related to motor learning (retention and transfer) and adaptation (predictable and unpredictable perturbations). Yet few studies have further investigated the underlying dynamics that may elicit these benefits. In this study, we investigated the effects of two levels of performance stabilization on motor performance and control while learning to intercept a virtual moving target. We randomly ided 40 participants of both sexes ( M age = 26.02 years, SD = 2.02) into a Stabilization Group (SG) and a Superstabilization Group (SSG). We considered the performance stabilized when a moving target was intercepted three times in a row and superstabilized when the same criterion was repeated six times. We analyzed outcome variables related to performance accuracy (absolute spatial error) and variability(coefficient of variation) and motor control (relative time to peak velocity-tPV% and its coefficient of variation) on both the first and last blocks of practice trials. Both groups showed comparable increases in performance accuracy from the first to the last block ( p = .001, η p 2 = 1.00), but SSG presented higher variability than SG ( p = .05, η p 2 = .70). Concerning motor control, both groups started the experiment with low tPV% and finished with comparably high tPV% and variability. Thus, although practicing two levels of performance stabilization led to similar performance accuracy and movement control, superstabilization resulted in higher performance variability with no loss of accuracy. Enhanced stabilization may increase the ability to adapt to environmental changes, but more research is needed to demonstrate this. These findings add to an understanding of the relationship between levels of performance stabilization and performance variability and may have implications for professional interventions (e.g. sports, rehabilitation) in considering the benefits of practice beyond performance stabilization.
Publisher: Public Library of Science (PLoS)
Date: 31-10-2018
Publisher: Springer Science and Business Media LLC
Date: 04-2019
Publisher: American Physical Society (APS)
Date: 29-10-2019
Publisher: AIP Publishing
Date: 08-2019
DOI: 10.1063/1.5093197
Abstract: Recurrence network analysis (RNA) is a remarkable technique for the detection of dynamical transitions in experimental applications. However, in practical experiments, often only a scalar time series is recorded. This requires the state-space reconstruction from this single time series which, as established by embedding and observability theory, is shown to be h ered if the recorded variable conveys poor observability. In this work, we investigate how RNA metrics are impacted by the observability properties of the recorded time series. Following the framework of Zou et al. [Chaos 20, 043130 (2010)], we use the Rössler and Duffing-Ueda systems as benchmark models for our study. It is shown that usually RNA metrics perform badly with variables of poor observability as for recurrence quantification analysis. An exception is the clustering coefficient, which is rather robust to observability issues. Along with its efficacy to detect dynamical transitions, it is shown to be an efficient tool for RNA—especially when no prior information of the variable observability is available.
Publisher: Elsevier BV
Date: 2016
Publisher: FapUNIFESP (SciELO)
Date: 03-2017
Publisher: SAGE Publications
Date: 18-08-2019
Abstract: Allowing learners to control feedback has been an effective strategy in motor skills learning. However, most studies of self-controlled (SC) feedback have used simple tasks that may be dissimilar to sports skills that generally demand more degrees of freedom and cognition. Thus, this study investigated the effects of SC knowledge of results (KR) on learning a complex Taekwondo skill. Twenty-four undergraduate volunteers of both sexes, aged 18-35 years, practiced a specific serial Taekwondo skill that was novel to them. We ided participants randomly into SC and yoked groups and compared their performance after they learned a specific displacement sequence, finishing with a lateral kick (bandal-tchagui) at a punching bag within a target time span. During acquisition, all participants performed 48 trials ided into six blocks and, on a retention test 24 hours later, they performed 10 more trials. We found that both groups reduced their errors from the first to the last block of the acquisition phase and that the SC group showed a better performance on the retention test, relative to the yoked control group. SC KR participants requested KR mainly after good trials, though they showed no statistically significant differences between trials with and without KR. Their inefficiency in estimating their own errors may have been due to task complexity, since many aspects of the task beyond its temporal requirement demanded the learners’ attention. Our results, using a novel Taekwondo serial skill, confirm and extend the benefits of SC KR from just simple motor learning in past studies to learning complex motor skills.
Publisher: Elsevier BV
Date: 09-2014
Publisher: SPE
Date: 12-11-2020
DOI: 10.2118/202379-MS
Abstract: One of the challenges faced by companies in the oil and gas industry is the difficulty in assessing and quantifying subsurface uncertainties when planning for hydrocarbon exploitation. A commonly employed approach is to use available exploration and appraisal data to produce a range of possible subsurface realisations, through which hydrocarbon production forecasts are generated. Prediction of hydrocarbon production from these simulations are then used to assess the viability of a planned development concept and the associated subsurface uncertainties. However, due to the sparsity of field data and unpredictability of underground geology coupled with the typically large dataset sizes, the ability to rapidly quantify prediction uncertainty and provide an overview of the range of underground geologies leaves much to be desired. Here we show that the application of a network science approach to oil production prediction data provides an intuitive way to visualize and assess reservoir uncertainty. A network transformation utilizing Pearson correlation and mean absolute error as similarity measures were applied to a dataset containing time series predictions of oil production for 10 wells simulated in 50 different subsurface realisations. Realisations were generated using a synthetic reservoir spanning 20 years of production. It was found that the network representation enabled the inference of reservoir uncertainty by simple visual inspection. Additionally, network measures such as the beta index were used with results supporting their viability in quantifying uncertainty. The application of clustering algorithms to the resulting networks was also shown to simplify the time series into component characteristic subsurface realisations. We propose a method to quantify subsurface uncertainties and create a simplified representation of the characteristic modes associated with a range of subsurface realisations, greatly reducing the time required to conduct a cursory analysis. Our results demonstrate how the application of network science ideas may be applied to provide new ways of analyzing production data and performace predictions. These methods provide an opportunity to further refine descriptions of uncertainty by incorporating stochastic elements into the network as well.
Publisher: Universidade de Sao Paulo, Agencia USP de Gestao da Informacao Academica (AGUIA)
Date: 19-12-2017
DOI: 10.11606/1807-5509201700010083
Abstract: Este estudo teve como objetivos avaliar o controle postural de jovens e idosos em relação à direção predominante e à área de deslocamento do centro de pressão, buscando verifi car se diferentes bases de suporte evidenciam diferenças entre os grupos para estas duas variáveis. A amostra foi composta por oito adultos jovens (22,6±2,33 anos) e oito idosos (75,4±5,7 anos), e a tarefa consistiu em permanecer de pé sobre uma plataforma de força por 30 segundos, em duas bases de suporte: normal (BSN) e semi-tandem (BSST), sendo realizadas três tentativas em cada uma delas. Avaliou-se as variáveis “área” e “direção” de oscilação, ambas derivadas no centro de pressão. Os resultados mostraram que idosos apresentaram maior oscilação corporal que jovens e a restrição na base de suporte liou a oscilação de ambos os grupos etários. Conclui-se que idosos e jovens apresentam comportamentos distintos em relação à oscilação corporal e que o aumento na difi culdade da tarefa é capaz de evidenciar parcialmente essas diferenças.
Publisher: American Physical Society (APS)
Date: 19-05-2016
Publisher: AIP Publishing
Date: 09-2016
DOI: 10.1063/1.4963013
Abstract: Multivariate singular spectrum analysis (M-SSA) was recently adapted to study systems of coupled oscillators. It does not require an a priori definition for phase nor detailed knowledge of the in idual oscillators, but it uses all the variables of each system. This aspect could be restrictive for practical applications, since usually just a few (sometimes only one) variables are measured. Based on dynamical systems and observability theories, we first show how to apply the M-SSA with only one variable and show the conditions to achieve good performance. Next, we provide numerical evidence that this single-variable approach enhances the explanatory power compared to the original M-SSA when computed with all the system variables. This could have important practical implications, as pointed out using benchmark oscillators.
Publisher: American Physical Society (APS)
Date: 12-03-2020
Publisher: Elsevier BV
Date: 06-2014
Publisher: FapUNIFESP (SciELO)
Date: 03-2017
Publisher: AIP Publishing
Date: 10-2017
DOI: 10.1063/1.4985291
Abstract: Observability is the property that enables recovering the state of a dynamical system from a reduced number of measured variables. In high-dimensional systems, it is therefore important to make sure that the variable recorded to perform the analysis conveys good observability of the system dynamics. The observability of a network of neuron models depends nontrivially on the observability of the node dynamics and on the topology of the network. The aim of this paper is twofold. First, to perform a study of observability using four well-known neuron models by computing three different observability coefficients. This not only clarifies observability properties of the models but also shows the limitations of applicability of each type of coefficients in the context of such models. Second, to study the emergence of phase synchronization in networks composed of neuron models. This is done performing multivariate singular spectrum analysis which, to the best of the authors' knowledge, has not been used in the context of networks of neuron models. It is shown that it is possible to detect phase synchronization: (i) without having to measure all the state variables, but only one (that provides greatest observability) from each node and (ii) without having to estimate the phase.
Publisher: AIP Publishing
Date: 08-2018
DOI: 10.1063/1.5020371
Abstract: Inappropriate patient-ventilator interactions' (PVI) quality is associated with adverse clinical consequences, such as patient anxiety/fear and increased need of sedative and paralytic agents. Thus, technological devices/tools to support the recognition and monitoring of different PVI quality are of great interest. In the present study, we investigate two tools based on a recent landmark study which applied recurrence plots (RPs) and recurrence quantification analysis (RQA) techniques in non-invasive mechanical ventilation. Our interest is in how this approach could be a daily part of critical care professionals' routine (which are not familiar with dynamical systems theory methods and concepts). Two representative time series of three typical PVI "scenarios" were selected from
No related grants have been discovered for Leonardo Santos.