Abstract

Abstract
This work addresses the problem of computing the time evolution of the probability density function (pdf) of the state in a nonlinear neuromuscular blockade (NMB) model, assuming that the source of uncertainty is the knowledge about one parameter. The NMB state is enlarged with the parameter, that verifies an equation given by its derivative being zero and has an initial condition described by a known pdf. By treating the resulting enlarged state-space model as a stochastic differential equation, the pdf of the state verifies a special case of the Fokker-Planck equation in which the second derivative terms vanish. This partial differential equation is solved with a numerical method based on Trotter’s formula for semigroup decomposition. The method is illustrated with results for a reduced complexity NMB model. A comparison of the predicted state pdf with clinical data for real patients is provided. © Springer International Publishing Switzerland 2014.

Abstract
This paper addresses the problem of joint estimation of the state and parameters for a deterministic continuous time system, with discrete time observations, in which the parameter vector is constant but its value is not known, being a random variable with a known distribution. Along time, the uncertainty in the parameter induces uncertainty in the plant state. The joint probability density function (pdf) satisfies the Liouville partial differential equation that is a limit case of the Fokker-Planck equation for vanishing diffusion. The continuous-discrete filter proposed operates as follows: Between two consecutive output sampling time instants, the pdf is propagated by solving the Liouville equation for an augmented state and is then corrected by using the last observation and Bayes law. An application to state estimation of the neuromuscular blockade of patients subject to general anesthesia, where parameter uncertainty is due to inter-patient variability, is described.

Abstract
During surgical interventions, a muscle relaxant drug is frequently administered with the objective of inducing muscle paralysis. Clinical environment and patient safety issues lead to a huge variety of situations that must be taken into account requiring intensive simulation studies. Hence, population models are crucial for research and development in this field.This work develops a stochastic population model for the neuromuscular blockade (NMB) (muscle paralysis) level induced by atracurium based on a deterministic individual model already proposed in the literature. To achieve this goal, a joint Lognormal distribution is considered for the patient-dependent parameters. This study is based on clinical data collected during general anaesthesia. The procedure developed enables to construct a reliable reference bank of parametrized models that not only reproduces the overall features of the NMB, but also the inter-individual variability characteristic of physiological signals. It turns out that this bank constitutes a fundamental tool to support research on identification and control algorithms and is suitable to be integrated in clinical decision support systems.

Abstract
Scand J Caring Sci; 2013; 27; 468474 Evaluation and cross-cultural adaptation of the Hendrich II Fall Risk Model to Portuguese Background: Several tools for the assessment of the risk of falling are used commonly by clinical nurses, but none have been validated in Portuguese. Aims: To adapt and evaluate the Hendrich II Fall Risk Model (HIIFRM) for use with elderly Portuguese inpatients. Method: We conducted a prospective study of 586 older inpatients in acute care hospitals, from November 2007 to May 2010. Results: The study involved 270 men and 316 women. The most frequent risk factor on admission and at discharge was a score 3 on the Get Up and Go' test. The adapted HIIFRM showed a sensitivity of 93.2% and 75.7%, and a specificity of 35% and 46.7%, on admission and at discharge, respectively. A positive predictive value of 17.2% on admission and 17% at discharge and a negative predictive value of 97.3% and 93%, respectively, were estimated. Conclusions: The HIIFRM was shown to be a useful tool in predicting falls by patients. Nevertheless, the research model suggested that only four risk factors affected the occurrence of falls significantly on admission and two risk factors at discharge. Further research is required in Portuguese hospital settings.

Abstract
Nowadays, wind energy has an important role in the challenges of clean energy supply. It is the fastest growing energy source with a increasing annual rate of 20%. This scenario motivate the development of an optimization design tool to find optimal layout for wind farms. This paper proposes a mathematical model to find the best electrical interconnection configuration of the wind farm turbines and the substation. The goal is to minimize the installation costs, that include cable cost and cable installation costs, considering technical constraints. This problem corresponds to a capacitated minimum spanning tree with additional constraints. The methodology proposed is applied in a real case study and the results are compared with the ground solution. © Springer International Publishing Switzerland 2014.