An electromyographic analysis of the deep cervical flexor muscles in performance of craniocervical flexion

Background and Purpose. This study evaluated an electromyographic technique for the measurement of muscle activity of the deep cervical flexor (DCF) muscles. Electromyographic signals were detected from the DCF, sternocleidomastoid (SCM), and anterior scalene (AS) muscles during performance of the craniocervical flexion (CCF) test, which involves performing 5 stages of increasing craniocervical flexion range of motion-the anatomical action of the DCF muscles. Subjects. Ten volunteers without known pathology or impairment participated in this study. Methods. Root-mean-square (RMS) values were calculated for the DCF, SCM, and AS muscles during performance of the CCF test. Myoelectric signals were recorded from the DCF muscles using bipolar electrodes placed over the posterior oropharyngeal wall. Reliability estimates of normalized RMS values were obtained by evaluating intraclass correlation coefficients and the normalized standard error of the mean (SEM). Results. A linear relationship was evident between the amplitude of DCF muscle activity and the incremental stages of the CCF test (F=239.04, df=36, P<.0001). Normalized SEMs in the range 6.7% to 10.3% were obtained for the normalized RMS values for the DCF muscles, providing evidence of reliability for these variables. Discussion and Conclusion. This approach for obtaining a direct measure of the DCF muscles, which differs from those previously used, may be useful for the examination of these muscles in future electromyographic applications.

Mean anisotropy of homogeneous Gaussian random fields and anisotropic norms of linear translation-invariant operators on multidimensional integer lattices

Sensitivity of output of a linear operator to its input can be quantified in various ways. In Control Theory, the input is usually interpreted as disturbance and the output is to be minimized in some sense. In stochastic worst-case design settings, the disturbance is considered random with imprecisely known probability distribution. The prior set of probability measures can be chosen so as to quantify how far the disturbance deviates from the white-noise hypothesis of Linear Quadratic Gaussian control. Such deviation can be measured by the minimal Kullback-Leibler informational divergence from the Gaussian distributions with zero mean and scalar covariance matrices. The resulting anisotropy functional is defined for finite power random vectors. Originally, anisotropy was introduced for directionally generic random vectors as the relative entropy of the normalized vector with respect to the uniform distribution on the unit sphere. The associated a-anisotropic norm of a matrix is then its maximum root mean square or average energy gain with respect to finite power or directionally generic inputs whose anisotropy is bounded above by a≥0. We give a systematic comparison of the anisotropy functionals and the associated norms. These are considered for unboundedly growing fragments of homogeneous Gaussian random fields on multidimensional integer lattice to yield mean anisotropy. Correspondingly, the anisotropic norms of finite matrices are extended to bounded linear translation invariant operators over such fields.

Rock fracture mean trace length estimation and confidence interval calculation using maximum likelihood methods

There has been a resurgence of interest in the mean trace length estimator of Pahl for window sampling of traces. The estimator has been dealt with by Mauldon and Zhang and Einstein in recent publications. The estimator is a very useful one in that it is non-parametric. However, despite some discussion regarding the statistical distribution of the estimator, none of the recent works or the original work by Pahl provide a rigorous basis for the determination a confidence interval for the estimator or a confidence region for the estimator and the corresponding estimator of trace spatial intensity in the sampling window. This paper shows, by consideration of a simplified version of the problem but without loss of generality, that the estimator is in fact the maximum likelihood estimator (MLE) and that it can be considered essentially unbiased. As the MLE, it possesses the least variance of all estimators and confidence intervals or regions should therefore be available through application of classical ML theory. It is shown that valid confidence intervals can in fact be determined. The results of the work and the calculations of the confidence intervals are illustrated by example. (C) 2003 Elsevier Science Ltd. All rights reserved.

The reliability of video based time motion analysis

Time motion analysis is extensively used to assess the demands of team sports. At present there is only limited information on the reliability of measurements using this analysis tool. The aim of this study was to establish the reliability of an individual observer's time motion analysis of rugby union. Ten elite level rugby players were individually tracked in Southern Hemisphere Super 12 matches using a digital video camera. The video footage was subsequently analysed by a single researcher on two occasions one month apart. The test-retest reliability was quantified as the typical error of measurement (TEM) and rated as either good (10% TEM). The total time spent in the individual movements of walking, jogging, striding, sprinting, static exertion and being stationary had moderate to poor reliability (5.8-11.1% TEM). The frequency of individual movements had good to poor reliability (4.3-13.6% TEM), while the mean duration of individual movements had moderate reliability (7.1-9.3% TEM). For the individual observer in the present investigation, time motion analysis was shown to be moderately reliable as an evaluation tool for examining the movement patterns of players in competitive rugby. These reliability values should be considered when assessing the movement patterns of rugby players within competition.

Poor correlation of mid-femoral measurements by CT and hip measurements by DXA in the elderly

Background and aims: Hip fracture is a devastating event in terms of outcome in the elderly, and the best predictor of hip fracture risk is hip bone density, usually measured by dual X-ray absorptiometry (DXA). However, bone density can also be ascertained from computerized tomography (CT) scans, and mid-thigh scans are frequently employed to assess the muscle and fat composition of the lower limb. Therefore, we examined if it was possible to predict hip bone density using mid-femoral bone density. Methods: Subjects were 803 ambulatory white and black women and men, aged 70-79 years, participating in the Health, Aging and Body Composition (Health ABC) Study. Bone mineral content (BMC, g) and volumetric bone mineral density (vBMD, mg/cm(3)) of the mid-femur were obtained by CT, whereas BMC and areal bone mineral density (aBMD, g/cm(2)) of the hip (femoral neck and trochanter) were derived from DXA. Results: In regression analyses stratified by race and sex, the coefficient of determination was low with mid-femoral BMC, explaining 6-27% of the variance in hip BMC, with a standard error of estimate (SEE) ranging from 16 to 22% of the mean. For mid-femur vBMD, the variance explained in hip aBMD was 2-17% with a SEE ranging from 15 to 18%. Adjusting aBMD to approximate volumetric density did not improve the relationships. In addition, the utility of fracture prediction was examined. Forty-eight subjects had one or more fractures (various sites) during a mean follow-up of 4.07 years. In logistic regression analysis, there was no association between mid-femoral vBMD and fracture (all fractures), whereas a 1 SD increase in hip BMD was associated with reduced odds for fracture of similar to60%. Conclusions: These results do not support the use of CT-derived mid-femoral vBMD or BMC to predict DXA-measured hip bone mineral status, irrespective of race or sex in older adults. Further, in contrast to femoral neck and trochanter BMD, mid-femur vBMD was not able to predict fracture (all fractures). (C) 2003, Editrice Kurtis.

Drying kinetics of jatropha seeds

Given the necessity of developing jatropha cultivation equipment, this work adjusted different mathematical models to experimental data obtained from the drying of jatropha seeds submitted to different drying conditions and selected the best model to describe the drying process. The experiment was carried out at the Federal Institute of Goiás - Rio Verde Campus. Seeds with initial moisture content of approximately 0.50 (kg water/kg dry matter) were dried in a forced air-ventilated oven, at temperatures of 45, 60, 75, 90 and 105°C to moisture content of 0.10 ± 0.005 (kg water/kg dry matter). The experimental data were adjusted to 11 mathematical models to represent the drying process of agricultural products. The models were compared using the coefficient of determination, chi-square test, relative mean error, estimated mean error and residual distribution. It was found that the increase in the air temperature caused a reduction in the drying time of seeds. The models Midilli and Two Terms were suitable to represent the drying process of Jatropha seeds and between them the use of the Midili model is recommended due to its greater simplicity.

Error bounds for low-rank approximations of the first exponential integral kernel

A hierarchical matrix is an efficient data-sparse representation of a matrix, especially useful for large dimensional problems. It consists of low-rank subblocks leading to low memory requirements as well as inexpensive computational costs. In this work, we discuss the use of the hierarchical matrix technique in the numerical solution of a large scale eigenvalue problem arising from a finite rank discretization of an integral operator. The operator is of convolution type, it is defined through the first exponential-integral function and, hence, it is weakly singular. We develop analytical expressions for the approximate degenerate kernels and deduce error upper bounds for these approximations. Some computational results illustrating the efficiency and robustness of the approach are presented.

Validity of self-reported weight: a study of urban brazilian adults

In order to evaluate the validity of self-reported weight for use in obesity prevalence surveys, self-reported weight was compared to measured weight for 659 adults living in the Porto Alegre county, RS Brazil in 1986-87, both weights being obtained by a technician in the individual's home on the same visit. The mean difference between self-reported and measured weight was small (-0.06 +/- 3.16 kg; mean +/- standard deviation), and the correlation between reported and measured weight was high (r=0.97). Sixty-two percent of participants reported their weight with an error of < 2 kg, 87% with an error of < 4 kg, and 95% with an error of < 6 kg. Underweight individuals overestimated their weight, while obese individuals underestimated theirs (p<0.05). Men tended to overestimate their weight and women underestimate theirs, this difference between sexes being statistically significant (p=0.04). The overall prevalence of underweight (body mass index < 20) by reported weight was 11%, by measured weight 13%; the overall prevalence of obesity (body mass index > 30) by reported weight was 10%, by measured weight 11%. Thus, the validity of reported weight is acceptable for surveys of the prevalence of ponderosity in similar settings.

Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

IGRT com CBCT: o impacto na precisão em radioterapia

Mestrado em Radiações Aplicadas às Tecnologias da Saúde.

3D-2D image registration by nonlinear regression

We propose a 3D-2D image registration method that relates image features of 2D projection images to the transformation parameters of the 3D image by nonlinear regression. The method is compared with a conventional registration method based on iterative optimization. For evaluation, simulated X-ray images (DRRs) were generated from coronary artery tree models derived from 3D CTA scans. Registration of nine vessel trees was performed, and the alignment quality was measured by the mean target registration error (mTRE). The regression approach was shown to be slightly less accurate, but much more robust than the method based on an iterative optimization approach.

Previsão de vento baseado em técnicas de Data Mining

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Desenvolvimento e validação de um sistema de recolha de sinal eletromiográfico baseado em placa de aquisição

A eletromiografia é, hoje em dia, uma das técnicas mais utilizadas no estudo dos músculos, estando presente em áreas como a medicina, a biomecânica e a fisiologia, possibilitando o desenvolvimento científico e contribuindo para proporcionar melhorias na qualidade da vida humana. Sendo assim, este trabalho apresenta um protótipo de um aparelho de aquisição de sinais eletromiográficos, explicando também toda a teoria, técnicas, componentes utilizadas e softwares que estiveram presentes na sua implementação. De uma forma sucinta, para a aquisição do sinal eletromiográfico usou-se uma placa de aquisição NI-USB 6009 e para a visualização do mesmo recorreu-se ao software LabVIEW. Para validar o sinal adquirido com o equipamento desenvolvido, utilizou-se um outro equipamento, o Biopac MP36 Student Lab System, fazendo-se assim recolhas de sinais eletromiográficos com ambos os equipamentos. Os sinais recolhidos pelos dois equipamentos foram analisados no software Acknowledge 3.9.0 (Biopac Systems, Inc.), podendo observar-se os espetros de frequência correspondentes a cada sinal e retirar valores para posterior análise estatística. Feita essa análise, concluiu-se que não foram detetadas diferenças significativas entre os sinais eletromiográficos recolhidos com ambos os equipamentos, validando-se assim, o equipamento desenvolvido.

Capillary bridging and long-range attractive forces in a mean-field approach

When a mixture is confined, one of the phases can condense out. This condensate, which is otherwise metastable in the bulk, is stabilized by the presence of surfaces. In a sphere-plane geometry, routinely used in atomic force microscope and surface force apparatus, it, can form a bridge connecting the surfaces. The pressure drop in the bridge gives rise to additional long-range attractive forces between them. By minimizing the free energy of a binary mixture we obtain the force-distance curves as well as the structural phase diagram of the configuration with the bridge. Numerical results predict a discontinuous transition between the states with and without the bridge and linear force-distance curves with hysteresis. We also show that similar phenomenon can be observed in a number of different systems, e.g., liquid crystals and polymer mixtures. (C). 2004 American Institute of Physics.