Accelerometer validity to measure and classify movement in team sports

 In team sports accelerometers are used to monitor the physical demands of athletic performance. Daniel's research showed that accelerometer accuracy can be improved through filtering. He also showed that the accelerometer can be used to automatically classify the type of movement performed. Further improving the understanding of team sports.

Nonparametric discovery of movement patterns from accelerometer signals

Monitoring daily physical activity plays an important role in disease prevention and intervention. This paper proposes an approach to monitor the body movement intensity levels from accelerometer data. We collect the data using the accelerometer in a realistic setting without any supervision. The ground-truth of activities is provided by the participants themselves using an experience sampling application running on their mobile phones. We compute a novel feature that has a strong correlation with the movement intensity. We use the hierarchical Dirichlet process (HDP) model to detect the activity levels from this feature. Consisting of Bayesian nonparametric priors over the parameters the model can infer the number of levels automatically. By demonstrating the approach on the publicly available USC-HAD dataset that includes ground-truth activity labels, we show a strong correlation between the discovered activity levels and the movement intensity of the activities. This correlation is further confirmed using our newly collected dataset. We further use the extracted patterns as features for clustering and classifying the activity sequences to improve performance.

Modulation of corticomotor excitability after maximal or sustainable-rate repetitive finger movement is impaired in Parkinson’s disease and is reversed by levodopa

Objectives: In healthy subjects, fatiguing exercises induce a period of post-exercise corticomotor depression (PECD) that is absent in Parkinson’s disease (PD). Our objective is to determine the time-course of corticomotor excitability changes following a 10-s repetitive index finger flexion–extension task performed at maximal voluntary rate (MVR) and a slower sustainable rate (MSR) in PD patients OFF and ON levodopa.
Methods: In 11 PD patients and 10 healthy age-matched controls, motor evoked potentials (MEPs) were recorded from the extensor indicis proprius (EIP) and first dorsal interosseous (FDI) muscles of the dominant arm immediately after the two tasks and at 2-min intervals for 10 min.
Results: In the OFF condition the PECD was absent in the two test muscles after both the MVR and MSR tasks. In the ON condition finger movement kinematics improved and a period of PECD comparable to that in controls was present after both tasks.
Conclusion: The absence of PECD in PD subjects off medication indicates a persisting increase in corticomotor excitability after non-fatiguing repetitive finger movement that is reversed by levodopa.

In search of academic identity : physical education, sport science and the field of human movement studies

This thesis addresses the problem of the academic identity of the area traditionally referred to as physical education. The study is a critical examination of the argu ments for the justi cation of this area as an autonomous branch of knowledge. The investigation concentrates on a selected number of arguments. The data collection comprised articles books and proceedings of conferences. The preliminary assessment of these materials resulted in a classi cation of the arguments into three groups. The rst group comprises the arguments in favour of physical education as an academic discipline. The second includes the arguments supporting a science of sport. The third consists of the arguments in favour of to a eld of human movement study. The examination of these arguments produced the following results. (a) The area of physical education does not satisfy the conditions presupposed by the de nition of academic discipline. This is so because the area does not form an integrated system of scienti c theories. (b) The same di culty emerges from the examination of the ar guments for sport science. There is no science of sport because there is no integrated system of scienti c theories related to sport. (c) The arguments in favour of a eld of study yielded more productive results. However di culties arise from the de nition of human movement. The analysis of this concept showed that its limits are not well demarcated. This makes it problematic to take human movement as the focus of a eld of studies. These aspects led to the conclusion that such things as an academic discipline of physical education sport science and eld of human movement studies do not exist. At least there are not such things in the sense of autonomous branches of knowledge. This does not imply that a more integrated inquiry based on several disciplines is not possible and desirable. This would enable someone entering phys ical education to nd a more organised structure of knowledge with some generally accepted problem situations procedures and theories on which to base professional practice.

Racial discrimination in Brazil: interviews with leaders of the black movement

Racism in Brazil has some specificities when compared to other countries, for, differently from, for instance, South Africa and the United States, Brazilian Constitutions, ever since the Independence (1822), have never distinguished the citizens according to race or color. Furthermore, since the mid-1900s, Afro-Brazilian cultural manifestations, such as, for example, samba and capoeira, started to be valued as a part of our “national identity”. These specificities make race relations in Brazilian society a much more complex issue. This paper is focused on selected parts of interviews that deal with the nature of racial discrimination in Brazil, extracted from interviews with leaders of the black movement produced within the scope of the project “The History of Black Movement in Brazil: organization of a collection of Oral History Interviews”, developed by CPDOC, Getulio Vargas Foundation (Rio de Janeiro). These “histories within history”, as told by our interviewees, may be transformed into images that will be able to condense a given reality, thus allowing us to evaluate the gains obtained by oral history methodology.

Forecasting multivariate time series under present-value-model short- and long-run co-movement restrictions

It is well known that cointegration between the level of two variables (e.g. prices and dividends) is a necessary condition to assess the empirical validity of a present-value model (PVM) linking them. The work on cointegration,namelyon long-run co-movements, has been so prevalent that it is often over-looked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. This amounts to investigate whether short-run co-movememts steming from common cyclical feature restrictions are also present in such a system. In this paper we test for the presence of such co-movement on long- and short-term interest rates and on price and dividend for the U.S. economy. We focuss on the potential improvement in forecasting accuracies when imposing those two types of restrictions coming from economic theory.

Forecasting Multivariate Time Series under Present-Value-Model Short- and Long-run Co-movement Restrictions

This paper has two original contributions. First, we show that the present value model (PVM hereafter), which has a wide application in macroeconomics and fi nance, entails common cyclical feature restrictions in the dynamics of the vector error-correction representation (Vahid and Engle, 1993); something that has been already investigated in that VECM context by Johansen and Swensen (1999, 2011) but has not been discussed before with this new emphasis. We also provide the present value reduced rank constraints to be tested within the log-linear model. Our second contribution relates to forecasting time series that are subject to those long and short-run reduced rank restrictions. The reason why appropriate common cyclical feature restrictions might improve forecasting is because it finds natural exclusion restrictions preventing the estimation of useless parameters, which would otherwise contribute to the increase of forecast variance with no expected reduction in bias. We applied the techniques discussed in this paper to data known to be subject to present value restrictions, i.e. the online series maintained and up-dated by Shiller. We focus on three different data sets. The fi rst includes the levels of interest rates with long and short maturities, the second includes the level of real price and dividend for the S&P composite index, and the third includes the logarithmic transformation of prices and dividends. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to them. Moreover, imposing short-run restrictions produce forecast winners 70% of the time for target variables of PVMs and 63.33% of the time when all variables in the system are considered.

Co-movement between two processes with local persistence

This paper introduces a residual based test where the null hypothesis of c:&InOvement between two processes with local persistenc~ can be tested, even under the presence of an endogenous regressor. It, therefore, fills in an existing lacuna in econometrics, in which longrun relationships can also be tested if the dependent and independent variables do not have a unit root, but do exhibit local persistence.

Forecasting multivariate time series under present-value-model short- and long-run co-movement restrictions

Using a sequence of nested multivariate models that are VAR-based, we discuss different layers of restrictions imposed by present-value models (PVM hereafter) on the VAR in levels for series that are subject to present-value restrictions. Our focus is novel - we are interested in the short-run restrictions entailed by PVMs (Vahid and Engle, 1993, 1997) and their implications for forecasting. Using a well-known database, kept by Robert Shiller, we implement a forecasting competition that imposes different layers of PVM restrictions. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to the unrestricted VAR. Moreover, imposing short-run restrictions produces forecast winners 70% of the time for the target variables of PVMs and 63.33% of the time when all variables in the system are considered.