913 resultados para GLUCOSE MONITORING-SYSTEM


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An auto-switch device has been designed, constructed, and tested for multisensor corrosion measurements. The auto-switch is able to connect/disconnect the selected wire beam electrode and/or electrode pairs under computer control. A computer controlled analog switch-array consisting of 100 inputs has been used as an essential part of the switch bank. The switch-bank is an essential component of a corrosion-monitoring instrument that is expected to find wide application in industry. The performance of the switch-bank is discussed and its effect on the signals is illustrated.

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Although the costs of parental care are at the foundations of optimal-parental-investment theory, our understanding of the nature of the underlying costs is limited by the difficulty of measuring variation in foraging effort. We simultaneously measured parental provisioning and foraging behavior in a free-living population of Zebra Finches (Taeniopygia guttata) using an electronic monitoring system. We fitted 145 adults with a passive transponder tag and remotely recorded their visits to nest boxes and feeders continuously over a 2-month period. After validating the accuracy of this monitoring system, we studied how provisioning and foraging activities varied through time (day and breeding cycle) and influenced the benefits (food received by the offspring) and costs (interclutch interval) of parental care. The provisioning rates of wild Zebra Finches were surprisingly low, with an average of only one visit per hour throughout the day. This was significantly lower than those reported for this model species in captivity and for most other passerines in the wild. Nest visitation rate only partially explained the amount of food received by the young, with parental foraging activity, including the minimum distance covered on foraging trips, being better predictors. Parents that sustained higher foraging activity and covered more distance during the first breeding attempt took longer to renest. These results demonstrate that in some species matching foraging activity with offspring provisioning may provide a better estimate of the true investment that individuals commit to a reproductive attempt.

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Stroke is a common neurological condition which is becoming increasingly common as the population ages. This entails healthcare monitoring systems suitable for home use, with remote access for medical professionals and emergency responders. The mobile phone is becoming the easy access tool for self-evaluation of health, but it is hindered by inherent problems including computational power and storage capacity. This research proposes a novel cloud based architecture of a biomedical system for a wearable motion kinematic analysis system which mitigates the above mentioned deficiencies of mobile devices. The system contains three subsystems: 1. Bio Kin WMS for measuring the acceleration and rotation of movement 2. Bio Kin Mobi for Mobile phone based data gathering and visualization 3. Bio Kin Cloud for data intensive computations and storage. The system is implemented as a web system and an android based mobile application. The web system communicates with the mobile application using an encrypted data structure containing sensor data and identifiable headings. The raw data, according to identifiable headings, is stored in the Amazon Relational Database Service which is automatically backed up daily. The system was deployed and tested in Amazon Web Services.

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Dynamic surface roughness prediction during metal cutting operations plays an important role to enhance the productivity in manufacturing industries. Various machining parameters such as unwanted noises affect the surface roughness, whatever their effects have not been adequately quantified. In this study, a general dynamic surface roughness monitoring system in milling operations was developed. Based on the experimentally acquired data, the milling process of Al 7075 and St 52 parts was simulated. Cutting parameters (i.e., cutting speed, feed rate, and depth of cut), material type, coolant fluid, X and Z components of milling machine vibrations, and white noise were used as inputs. The original objective in the development of a dynamic monitoring system is to simulate wide ranges of machining conditions such as rough and finishing of several materials with and without cutting fluid. To achieve high accuracy of the resultant data, the full factorial design of experiment was used. To verify the accuracy of the proposed model, testing and recall/verification procedures have been carried out and results showed that the accuracy of 99.8 and 99.7 % were obtained for testing and recall processes.

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This article presents a new method to detect damage in structures based on the electromechanical impedance principle. The system follows the variations in the output voltage of piezoelectric transducers and does not compute the impedance itself. The proposed system is portable, autonomous, versatile, and could efficiently replace commercial instruments in different structural health monitoring applications. The identification of damage is performed by simply comparing the variations of root mean square voltage from response signals of piezoelectric transducers, such as lead zirconate titanate patches bonded to the structure, obtained for different frequencies of the excitation signal. The proposed system is not limited by the sampling rate of analog-to-digital converters, dispenses Fourier transform algorithms, and does not require a computer for processing, operating autonomously. A low-cost prototype based on microcontroller and digital synthesizer was built, and experiments were carried out on an aluminum structure and excellent results have been obtained. © The Author(s) 2012.

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The Pierre Auger Observatory is a facility built to detect air showers produced by cosmic rays above 10(17) eV. During clear nights with a low illuminated moon fraction, the UV fluorescence light produced by air showers is recorded by optical telescopes at the Observatory. To correct the observations for variations in atmospheric conditions, atmospheric monitoring is performed at regular intervals ranging from several minutes (for cloud identification) to several hours (for aerosol conditions) to several days (for vertical profiles of temperature, pressure, and humidity). In 2009, the monitoring program was upgraded to allow for additional targeted measurements of atmospheric conditions shortly after the detection of air showers of special interest, e. g., showers produced by very high-energy cosmic rays or showers with atypical longitudinal profiles. The former events are of particular importance for the determination of the energy scale of the Observatory, and the latter are characteristic of unusual air shower physics or exotic primary particle types. The purpose of targeted (or "rapid") monitoring is to improve the resolution of the atmospheric measurements for such events. In this paper, we report on the implementation of the rapid monitoring program and its current status. The rapid monitoring data have been analyzed and applied to the reconstruction of air showers of high interest, and indicate that the air fluorescence measurements affected by clouds and aerosols are effectively corrected using measurements from the regular atmospheric monitoring program. We find that the rapid monitoring program has potential for supporting dedicated physics analyses beyond the standard event reconstruction.

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Nowadays, there is an increasing interest in wireless sensor networks (WSN) for environmental monitoring systems because it can be used to improve the quality of life and living conditions are becoming a major concern to people. This paper describes the design and development of a real time monitoring system based on ZigBee WSN characterized by a lower energy consumption, low cost, reduced dimensions and fast adaptation to the network tree topology. The developed system encompasses an optimized sensing process about environmental parameters, low rate transmission from sensor nodes to the gateway, packet parsing and data storing in a remote database and real time visualization through a web server.

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EUMETSAT (www.eumetsat.int) e’ l’agenzia europea per operazioni su satelliti per monitorare clima, meteo e ambiente terrestre. Dal centro operativo situato a Darmstadt (Germania), si controllano satelliti meteorologici su orbite geostazionarie e polari che raccolgono dati per l’osservazione dell’atmosfera, degli oceani e della superficie terrestre per un servizio continuo di 24/7. Un sistema di monitoraggio centralizzato per programmi diversi all’interno dell’ambiente operazionale di EUMETSAT, e’ dato da GEMS (Generic Event Monitoring System). Il software garantisce il controllo di diverse piattaforme, cross-monitoring di diverse sezioni operative, ed ha le caratteristiche per potere essere esteso a future missioni. L’attuale versione della GEMS MMI (Multi Media Interface), v. 3.6, utilizza standard Java Server Pages (JSP) e fa uso pesante di codici Java; utilizza inoltre files ASCII per filtri e display dei dati. Conseguenza diretta e’ ad esempio, il fatto che le informazioni non sono automaticamente aggiornate, ma hanno bisogno di ricaricare la pagina. Ulteriori inputs per una nuova versione della GEMS MMI vengono da diversi comportamenti anomali riportati durante l’uso quotidiano del software. La tesi si concentra sulla definizione di nuovi requisiti per una nuova versione della GEMS MMI (v. 4.4) da parte della divisione ingegneristica e di manutenzione di operazioni di EUMETSAT. Per le attivita’ di supporto, i test sono stati condotti presso Solenix. Il nuovo software permettera’ una migliore applicazione web, con tempi di risposta piu’ rapidi, aggiornamento delle informazioni automatico, utilizzo totale del database di GEMS e le capacita’ di filtri, insieme ad applicazioni per telefoni cellulari per il supporto delle attivita’ di reperibilita’. La nuova versione di GEMS avra’ una nuova Graphical User Interface (GUI) che utilizza tecnologie moderne. Per un ambiente di operazioni come e’ quello di EUMETSAT, dove l’affidabilita’ delle tecnologie e la longevita’ dell’approccio scelto sono di vitale importanza, non tutti gli attuali strumenti a disposizione sono adatti e hanno bisogno di essere migliorati. Allo stesso tempo, un’ interfaccia moderna, in termini di visual design, interattivita’ e funzionalita’, e’ importante per la nuova GEMS MMI.

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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.

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Self-monitoring of blood glucose plays an important role in the management of diabetes and has been shown to improve metabolic control. The use of blood glucose meters in clinical practice requires sufficient reliability to allow adequate treatment. Direct comparison of different blood glucose meters in clinical practice, independent of the manufactures is scarce. We, therefore, aimed to evaluate three frequently used blood glucose meters in daily clinical practice.

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Abstract Background and Aims: Data on the influence of calibration on accuracy of continuous glucose monitoring (CGM) are scarce. The aim of the present study was to investigate whether the time point of calibration has an influence on sensor accuracy and whether this effect differs according to glycemic level. Subjects and Methods: Two CGM sensors were inserted simultaneously in the abdomen on either side of 20 individuals with type 1 diabetes. One sensor was calibrated predominantly using preprandial glucose (calibration(PRE)). The other sensor was calibrated predominantly using postprandial glucose (calibration(POST)). At minimum three additional glucose values per day were obtained for analysis of accuracy. Sensor readings were divided into four categories according to the glycemic range of the reference values (low, ≤4 mmol/L; euglycemic, 4.1-7 mmol/L; hyperglycemic I, 7.1-14 mmol/L; and hyperglycemic II, >14 mmol/L). Results: The overall mean±SEM absolute relative difference (MARD) between capillary reference values and sensor readings was 18.3±0.8% for calibration(PRE) and 21.9±1.2% for calibration(POST) (P<0.001). MARD according to glycemic range was 47.4±6.5% (low), 17.4±1.3% (euglycemic), 15.0±0.8% (hyperglycemic I), and 17.7±1.9% (hyperglycemic II) for calibration(PRE) and 67.5±9.5% (low), 24.2±1.8% (euglycemic), 15.5±0.9% (hyperglycemic I), and 15.3±1.9% (hyperglycemic II) for calibration(POST). In the low and euglycemic ranges MARD was significantly lower in calibration(PRE) compared with calibration(POST) (P=0.007 and P<0.001, respectively). Conclusions: Sensor calibration predominantly based on preprandial glucose resulted in a significantly higher overall sensor accuracy compared with a predominantly postprandial calibration. The difference was most pronounced in the hypo- and euglycemic reference range, whereas both calibration patterns were comparable in the hyperglycemic range.