27 resultados para physiologic stages


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Pulse Transit Time (PTT) measurement has showed potential in non-invasive monitoring of changes in blood pressure. In children, the common peripheral sites used for these studies are a finger or toe. Presently, there are no known studies conducted to investigate any possible physiologic parameters affecting PTT measurement at these sites for children. In this study, PTT values of both peripheral sites were recorded from 64 children in their sitting posture. Their mean age with standard deviation (SD) was 8.2 2.6years (ranged 3 to 12years). Subjects' peripheries path length, heart rate (HR), systolic (SBP) and diastolic blood pressure (DBP) were measured to investigate any contributions to PTT measurement. The peripheral pulse timing characteristic measured by photoplethysmography (PPG) shows a 59.5 8.5ms (or 24.8 0.4%) difference between the two peripheries (p

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Pulse transit time (PTT) is a non-invasive measure, defined as time taken for the pulse pressure waves to travel from the R-wave of electrocardiogram to a selected peripheral site. Baseline PTT value is known to be influenced by physiologic variables like heart rate (HR), blood pressure (BP) and arterial compliance (AC). However, few quantitative data are available describing the factors which can influence PTT measurements in a child during breathing. The aim of this study was to investigate the effects of changes in breathing efforts on PTT baseline and fluctuations. Two different inspiratory resistive loading (IRL) devices were used to simulate loaded breathing in order to induce these effects. It is known that HR can influence the normative PTT value however the effect of HR variability (HRV) is not well-studied. Two groups of 3 healthy children ( 0.05) HR changes during all test activities. Results showed that HRV is not the sole contributor to PTT variations and suggest that changes in other physiologic parameters are also equally important. Hence, monitoring PTT measurement can be indicative of these associated changes during tidal or increased breathing efforts in healthy children.

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In this paper we propose a fast adaptive Importance Sampling method for the efficient simulation of buffer overflow probabilities in queueing networks. The method comprises three stages. First we estimate the minimum Cross-Entropy tilting parameter for a small buffer level; next, we use this as a starting value for the estimation of the optimal tilting parameter for the actual (large) buffer level; finally, the tilting parameter just found is used to estimate the overflow probability of interest. We recognize three distinct properties of the method which together explain why the method works well; we conjecture that they hold for quite general queueing networks. Numerical results support this conjecture and demonstrate the high efficiency of the proposed algorithm.