24 resultados para continuous biometric authentication system
em BORIS: Bern Open Repository and Information System - Berna - Suiça
Resumo:
This work presents a new, field-deployable technique for continuous, high-resolution measurements of methane mixing ratios from ice cores. The technique is based on a continuous flow analysis system, where ice core samples cut along the long axis of an ice core are melted continuously. The past atmospheric air contained in the ice is separated from the melt water stream via a system for continuous gas extraction. The extracted gas is dehumidified and then analyzed by a Wavelength Scanned-Cavity Ring Down Spectrometer for methane mixing ratios. We assess the performance of the new measurement technique in terms of precision (±0.8 ppbv, 1σ), accuracy (±8 ppbv), temporal (ca. 100 s), and spatial resolution (ca. 5 cm). Using a firn air transport model, we compare the resolution of the measurement technique to the resolution of the atmospheric methane signal as preserved in ice cores in Greenland. We conclude that our measurement technique can resolve all climatically relevant variations as preserved in the ice down to an ice depth of at least 1980 m (66 000 yr before present) in the North Greenland Eemian Ice Drilling ice core. Furthermore, we describe the modifications, which are necessary to make a commercially available spectrometer suitable for continuous methane mixing ratio measurements from ice cores.
Resumo:
SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patient's related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patient's data, supporting the physician in decision making, regarding the patient's treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patient's glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platform's evaluation in clinical environment is being in progress.
Resumo:
In this paper two models for the simulation of glucose-insulin metabolism of children with Type 1 diabetes are presented. The models are based on the combined use of Compartmental Models (CMs) and artificial Neural Networks (NNs). Data from children with Type 1 diabetes, stored in a database, have been used as input to the models. The data are taken from four children with Type 1 diabetes and contain information about glucose levels taken from continuous glucose monitoring system, insulin intake and food intake, along with corresponding time. The influences of taken insulin on plasma insulin concentration, as well as the effect of food intake on glucose input into the blood from the gut, are estimated from the CMs. The outputs of CMs, along with previous glucose measurements, are fed to a NN, which provides short-term prediction of glucose values. For comparative reasons two different NN architectures have been tested: a Feed-Forward NN (FFNN) trained with the back-propagation algorithm with adaptive learning rate and momentum, and a Recurrent NN (RNN), trained with the Real Time Recurrent Learning (RTRL) algorithm. The results indicate that the best prediction performance can be achieved by the use of RNN.
Resumo:
The aim of this study was to document experience gained with herd health management in veal calf production and to describe the calves' most frequent health problems. Fifteen farms with an 'all-in-all-out' animal flow system and 20 farms with a continuous animal flow system were investigated and data on animal movements, housing, feeding, medical treatments, and management were collected. Cadavers underwent pathological examination, and data were recorded from the carcasses of slaughtered calves. On the 15 'all-in-all-out'-farms, 2'747 calves were clinically examined by the contract-veterinarian upon arrival at the farm, and 71,1 % of the calves showed at least one sign of illness. The main causes of death were with 54,9 % digestive disorders (a perforating abomasal ulcer being the most frequent diagnosis), followed by respiratory diseases (29,6 %, mainly pneumonia). The meat color of 25 % of the carcasses was red. Calves from farms with the continuous animal flow system, which recruit mainly animals originating from the same farm, showed significantly better results regarding antibiotic use, performance and carcass quality than those calves from farms with the 'all-in-all-out'-system.
Resumo:
To measure surrogate markers of coagulation activation as well as of the systemic inflammatory response in patients undergoing primary elective coronary artery bypass grafting (CABG) using either the so-called Smart suction device or a continuous autotransfusion system (C.A.T.S.®).
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This paper aims at the development and evaluation of a personalized insulin infusion advisory system (IIAS), able to provide real-time estimations of the appropriate insulin infusion rate for type 1 diabetes mellitus (T1DM) patients using continuous glucose monitors and insulin pumps. The system is based on a nonlinear model-predictive controller (NMPC) that uses a personalized glucose-insulin metabolism model, consisting of two compartmental models and a recurrent neural network. The model takes as input patient's information regarding meal intake, glucose measurements, and insulin infusion rates, and provides glucose predictions. The predictions are fed to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. An algorithm based on fuzzy logic has been developed for the on-line adaptation of the NMPC control parameters. The IIAS has been in silico evaluated using an appropriate simulation environment (UVa T1DM simulator). The IIAS was able to handle various meal profiles, fasting conditions, interpatient variability, intraday variation in physiological parameters, and errors in meal amount estimations.
Resumo:
The purpose of this study was to evaluate the effect of continuously released BDNF on peripheral nerve regeneration in a rat model. Initial in vitro evaluation of calcium alginate prolonged-release-capsules (PRC) proved a consistent release of BDNF for a minimum of 8 weeks. In vivo, a worst case scenario was created by surgical removal of a 20-mm section of the sciatic nerve of the rat. Twenty-four autologous fascia tubes were filled with calcium alginate spheres and sutured to the epineurium of both nerve ends. The animals were divided into 3 groups. In group 1, the fascial tube contained plain calcium alginate spheres. In groups 2 and 3, the fascial tube contained calcium alginate spheres with BDNF alone or BDNF stabilized with bovine serum albumin, respectively. The autocannibalization of the operated extremity was clinically assessed and documented in 12 additional rats. The regeneration was evaluated histologically at 4 weeks and 10 weeks in a blinded manner. The length of nerve fibers and the numbers of axons formed in the tube was measured. Over a 10-week period, axons have grown significantly faster in groups 2 and 3 with continuously released BDNF compared to the control. The rats treated with BDNF (groups 2 and 3) demonstrated significantly less autocannibalization than the control group (group 1). These results suggest that BDNF may not only stimulate faster peripheral nerve regeneration provided there is an ideal, biodegradable continuous delivery system but that it significantly reduces the neuropathic pain in the rat model.
Resumo:
Auditory neuroscience has not tapped fMRI's full potential because of acoustic scanner noise emitted by the gradient switches of conventional echoplanar fMRI sequences. The scanner noise is pulsed, and auditory cortex is particularly sensitive to pulsed sounds. Current fMRI approaches to avoid stimulus-noise interactions are temporally inefficient. Since the sustained BOLD response to pulsed sounds decreases with repetition rate and becomes minimal with unpulsed sounds, we developed an fMRI sequence emitting continuous rather than pulsed gradient sound by implementing a novel quasi-continuous gradient switch pattern. Compared to conventional fMRI, continuous-sound fMRI reduced auditory cortex BOLD baseline and increased BOLD amplitude with graded sound stimuli, short sound events, and sounds as complex as orchestra music with preserved temporal resolution. Response in subcortical auditory nuclei was enhanced, but not the response to light in visual cortex. Finally, tonotopic mapping using continuous-sound fMRI demonstrates that enhanced functional signal-to-noise in BOLD response translates into improved spatial separability of specific sound representations.
Resumo:
BACKGROUND: The Anesthetic Conserving Device (AnaConDa) uncouples delivery of a volatile anesthetic (VA) from fresh gas flow (FGF) using a continuous infusion of liquid volatile into a modified heat-moisture exchanger capable of adsorbing VA during expiration and releasing adsorbed VA during inspiration. It combines the simplicity and responsiveness of high FGF with low agent expenditures. We performed in vitro characterization of the device before developing a population pharmacokinetic model for sevoflurane administration with the AnaConDa, and retrospectively testing its performance (internal validation). MATERIALS AND METHODS: Eighteen females and 20 males, aged 31-87, BMI 20-38, were included. The end-tidal concentrations were varied and recorded together with the VA infusion rates into the device, ventilation and demographic data. The concentration-time course of sevoflurane was described using linear differential equations, and the most suitable structural model and typical parameter values were identified. The individual pharmacokinetic parameters were obtained and tested for covariate relationships. Prediction errors were calculated. RESULTS: In vitro studies assessed the contribution of the device to the pharmacokinetic model. In vivo, the sevoflurane concentration-time courses on the patient side of the AnaConDa were adequately described with a two-compartment model. The population median absolute prediction error was 27% (interquartile range 13-45%). CONCLUSION: The predictive performance of the two-compartment model was similar to that of models accepted for TCI administration of intravenous anesthetics, supporting open-loop administration of sevoflurane with the AnaConDa. Further studies will focus on prospective testing and external validation of the model implemented in a target-controlled infusion device.
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Continuous intraperitoneal insulin infusion (CIPII) with the DiaPort system using regular insulin was compared to continuous subcutaneous insulin infusion (CSII) using insulin Lispro, to investigate the frequency of hypoglycemia, blood glucose control, quality of life, and safety.
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In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.
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Coulometric nanotitrations were realized in a microchannel system using a continuous-flow titration technique with a triangle current-time profile. Redox and acid-base titrations were carried out on Fe(II) and nitric acid samples, respectively, with the same nanotitrator device. A linear relation between the concentration and the coulometric current transferred to the solution was found. The advantages of this universally applicable nanotitrator are fast response, low sample volume, high sensitivity, and high reproducibility as well as the convenience of handling an automated analyzer of the flow-through type.
Resumo:
Recent outstanding clinical advances with new mechanical circulatory systems have led to additional strategies in the treatment of end-stage heart failure. Heart transplantation can be postponed and for certain patients even replaced by smaller implantable left ventricular assist devices (LVADs). Mechanical support of the failing left ventricle enables appropriate haemodynamic stabilization and recovery of secondary organ failure, often seen in these severely ill patients. These new devices may be of great help to bridge patients until a suitable cardiac allograft is available but are also discussed as definitive treatment for patients who do not qualify for transplantation. Main indications for LVAD implantation are bridge to recovery, bridge to transplantation or destination therapy. An LVAD may be an important tool for patients with an expected prolonged period on the waiting list, for instance those with blood group O or B, with high or low body weight and those with potentially reversible secondary organ failure and pulmonary artery hypertension. However, LVAD implantation means an additional heart operation with inherent perioperative risks and complications during the waiting period. Finally, cardiac transplantation in patients with prior implantation of an LVAD represents a surgical challenge. The care of patients after the implantation of miniaturized LVADs, such as the HeartWare® system, seems to be easier than following pulsatile devices. The explantation of such devices at the time of transplantation is technically more comfortable than after HeartMate II implantation.