Desempenho de pacientes com acidente vascular encefalico em testes de reconhecimento de tividades de vida diaria com frequencia autocontrolada e pre- determinada Luciana Protásio de Melo Natal 2009

The stimulation of motor learning is an important component to a rehabilitation and type of practice used is de basic importance to Physiotherapy. The motor skills are the types more basic of behavior that subjects must acquire throughout its lives and observational learning one of forms for its acquisition. Objective: This study aimed to compare performance of patients post- stroke on test of recognition of activities of day life using self-controlled and externally determined practice. Intervention: Forty subjects had been evaluated, 20 stroke patients (the mean age was 57,9?}6,7 years, schooling 6,7?}3,09 years and time of injury 23,4?}17,2 months) and 20 health subjects (the mean age 55,4?}5,9 years and schooling 8?}3,7 years). All was evaluated about independence functional (FIM) and cognitive state (MMSE), and patients were also evaluated about neurologic state (NIHSS). Later, all realized a recognition of activities of day life test (drink water and speak to telephone) on self-controlled (PAUTO and CAUTO) and externally determined (P20 and C20) frequency. The stroke subjects also were examined for a three-dimensional system of kinematic analysis, when they have drink water. The statistic analysis was realized for chi-square and t Student tests. Results: This was not difference, about number of rightness, between groups of self-controlled and externally determined practice (p0,005), and also not between patients and control groups (p0,005). Patients mean velocity (PAUTO: 141,1mm/sec and P20: 141,6mm/sec) and peak velocity (PAUTO: 652,1mm/sec and P20: 598,6mm/sec) were reduced, as well as the angles reached for elbow (PAUTO: 66,60 and 124,40; P20: 66,30 and 128,50 extension e flexion respectively) regarding literature. Conclusions: The performance on recognition of activities of day life test was similar between on self-controlled and externally determined frequency, showing both technique may be used to stimulate motor learning on chronic patients after stroke

Espectroscopia no infravermelho próximo e métodos de calibração multivariada aplicados à determinação simultânea de parâmetros bioquímicos em plasma sanguíneo

In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma