949 resultados para ELECTRICAL-RESISTANCE SENSOR


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Tracking or target localization is used in a wide range of important tasks from knowing when your flight will arrive to ensuring your mail is received on time. Tracking provides the location of resources enabling solutions to complex logistical problems. Wireless Sensor Networks (WSN) create new opportunities when applied to tracking, such as more flexible deployment and real-time information. When radar is used as the sensing element in a tracking WSN better results can be obtained; because radar has a comparatively larger range both in distance and angle to other sensors commonly used in WSNs. This allows for less nodes deployed covering larger areas, saving money. In this report I implement a tracking WSN platform similar to what was developed by Lim, Wang, and Terzis. This consists of several sensor nodes each with a radar, a sink node connected to a host PC, and a Matlab© program to fuse sensor data. I have re-implemented their experiment with my WSN platform for tracking a non-cooperative target to verify their results and also run simulations to compare. The results of these tests are discussed and some future improvements are proposed.

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This work presents an innovative integration of sensing and nano-scaled fluidic actuation in the combination of pH sensitive optical dye immobilization with the electro-osmotic phenomena in polar solvents like water for flow-through pH measurements. These flow-through measurements are performed in a flow-through sensing device (FTSD) configuration that is designed and fabricated at MTU. A relatively novel and interesting material, through-wafer mesoporous silica substrates with pore diameters of 20 -200 nm and pore depths of 500 µm are fabricated and implemented for electro-osmotic pumping and flow-through fluorescence sensing for the first time. Performance characteristics of macroporous silicon (> 500 µm) implemented for electro-osmotic pumping include, a very large flow effciency of 19.8 µLmin-1V-1 cm-2 and maximum pressure effciency of 86.6 Pa/V in comparison to mesoporous silica membranes with 2.8 µLmin-1V-1cm-2 flow effciency and a 92 Pa/V pressure effciency. The electrical current (I) of the EOP system for 60 V applied voltage utilizing macroporous silicon membranes is 1.02 x 10-6A with a power consumption of 61.74 x 10-6 watts. Optical measurements on mesoporous silica are performed spectroscopically from 300 nm to 1000 nm using ellipsometry, which includes, angularly resolved transmission and angularly resolved reflection measurements that extend into the infrared regime. Refractive index (n) values for oxidized and un-oxidized mesoporous silicon sample at 1000 nm are found to be 1.36 and 1.66. Fluorescence results and characterization confirm the successful pH measurement from ratiometric techniques. The sensitivity measured for fluorescein in buffer solution is 0.51 a.u./pH compared to sensitivity of ~ 0.2 a.u./pH in the case of fluorescein in porous silica template. Porous silica membranes are efficient templates for immobilization of optical dyes and represent a promising method to increase sensitivity for small variations in chemical properties. The FTSD represents a device topology suitable for application to long term monitoring of lakes and reservoirs. Unique and important contributions from this work include fabrication of a through-wafer mesoporous silica membrane that has been thoroughly characterized optically using ellipsometry. Mesoporous silica membranes are tested as a porous media in an electro-osmotic pump for generating high pressure capacities due to the nanometer pore sizes of the porous media. Further, dye immobilized mesoporous silica membranes along with macroporous silicon substrates are implemented for continuous pH measurements using fluorescence changes in a flow-through sensing device configuration. This novel integration and demonstration is completely based on silicon and implemented for the first time and can lead to miniaturized flow-through sensing systems based on MEMS technologies.

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Gas sensors have been used widely in different important area including industrial control, environmental monitoring, counter-terrorism and chemical production. Micro-fabrication offers a promising way to achieve sensitive and inexpensive gas sensors. Over the years, various MEMS gas sensors have been investigated and fabricated. One significant type of MEMS gas sensors is based on mass change detection and the integration with specific polymer. This dissertation aims to make contributions to the design and fabrication of MEMS resonant mass sensors with capacitance actuation and sensing that lead to improved sensitivity. To accomplish this goal, the research has several objectives: (1) Define an effective measure for evaluating the sensitivity of resonant mass devices; (2) Model the effects of air damping on microcantilevers and validate models using laser measurement system (3) Develop design guidelines for improving sensitivity in the presence of air damping; (4) Characterize the degree of uncertainty in performance arising from fabrication variation for one or more process sequences, and establish design guidelines for improved robustness. Work has been completed toward these objectives. An evaluation measure has been developed and compared to an RMS based measure. Analytic models of air damping for parallel plate that include holes are compared with a COMSOL model. The models have been used to identify cantilever design parameters that maximize sensitivity. Additional designs have been modeled with COMSOL and the development of an analytical model for Fixed-free cantilever geometries with holes has been developed. Two process flows have been implemented and compared. A number of cantilever designs have been fabricated and the uncertainty in process has been investigated. Variability from processing have been evaluated and characterized.

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Wireless sensor network is an emerging research topic due to its vast and ever-growing applications. Wireless sensor networks are made up of small nodes whose main goal is to monitor, compute and transmit data. The nodes are basically made up of low powered microcontrollers, wireless transceiver chips, sensors to monitor their environment and a power source. The applications of wireless sensor networks range from basic household applications, such as health monitoring, appliance control and security to military application, such as intruder detection. The wide spread application of wireless sensor networks has brought to light many research issues such as battery efficiency, unreliable routing protocols due to node failures, localization issues and security vulnerabilities. This report will describe the hardware development of a fault tolerant routing protocol for railroad pedestrian warning system. The protocol implemented is a peer to peer multi-hop TDMA based protocol for nodes arranged in a linear zigzag chain arrangement. The basic working of the protocol was derived from Wireless Architecture for Hard Real-Time Embedded Networks (WAHREN).

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The authors describe the design, fabrication, and testing of a passive wireless sensor platform utilizing low-cost commercial surface acoustic wave filters and sensors. Polyimide and polyethylene terephthalate sheets are used as substrates to create a flexible sensor tag that can be applied to curved surfaces. A microfabricated antenna is integrated on the substrate in order to create a compact form factor. The sensor tags are fabricated using 315 MHz surface acoustic wave filters and photodiodes and tested with the aid of a fiber-coupled tungsten lamp. Microwave energy transmitted from a network analyzer is used to interrogate the sensor tag. Due to an electrical impedance mismatch at the SAW filter and sensor, energy is reflected at the sensor load and reradiated from the integrated antenna. By selecting sensors that change electrical impedance based on environmental conditions, the sensor state can be inferred through measurement of the reflected energy profile. Testing has shown that a calibrated system utilizing this type of sensor tag can detect distinct light levels wireless and passively. The authors also demonstrate simultaneous operation of two tags with different center passbands that detects light. Ranging tests show that the sensor tags can operate at a distance of at least 3.6 m.

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BACKGROUND: Complete investigation of thrombophilic or hemorrhagic clinical presentations is a time-, apparatus-, and cost-intensive process. Sensitive screening tests for characterizing the overall function of the hemostatic system, or defined parts of it, would be very useful. For this purpose, we are developing an electrochemical biosensor system that allows measurement of thrombin generation in whole blood as well as in plasma. METHODS: The measuring system consists of a single-use electrochemical sensor in the shape of a strip and a measuring unit connected to a personal computer, recording the electrical signal. Blood is added to a specific reagent mixture immobilized in dry form on the strip, including a coagulation activator (e.g., tissue factor or silica) and an electrogenic substrate specific to thrombin. RESULTS: Increasing thrombin concentrations gave standard curves with progressively increasing maximal current and decreasing time to reach the peak. Because the measurement was unaffected by color or turbidity, any type of blood sample could be analyzed: platelet-poor plasma, platelet-rich plasma, and whole blood. The test strips with the predried reagents were stable when stored for several months before testing. Analysis of the combined results obtained with different activators allowed discrimination between defects of the extrinsic, intrinsic, and common coagulation pathways. Activated protein C (APC) predried on the strips allowed identification of APC-resistance in plasma and whole blood samples. CONCLUSIONS: The biosensor system provides a new method for assessing thrombin generation in plasma or whole blood samples as small as 10 microL. The assay is easy to use, thus allowing it to be performed in a point-of-care setting.

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OBJECTIVE: To determine the minimum alveolar concentration (MAC) of isoflurane in Shetland ponies using a sequence of three different supramaximal noxious stimulations at each tested concentration of isoflurane rather than a single stimulation. STUDY DESIGN: Prospective, experimental trial. ANIMALS: Seven 4-year-old, gelding Shetland ponies. METHODS: The MAC of isoflurane was determined for each pony. Three different modes of electrical stimulation were applied consecutively (2 minute intervals): two using constant voltage (90 V) on the gingiva via needle- (CVneedle) or surface-electrodes (CVsurface) and one using constant current (CC; 40 mA) via surface electrodes applied to the skin over the digital nerve. The ability to clearly interpret the responses as positive, the latency of the evoked responses and the inter-electrode resistance were recorded for each stimulus. RESULTS: Individual isoflurane MAC (%) values ranged from 0.60 to 1.17 with a mean (+/-SD) of 0.97 (+/-0.17). The responses were more clearly interpreted with CC, but did not reach statistical significance. The CVsurface mode produced responses with a longer delay. The CVneedle mode was accompanied by variable inter-electrode resistances resulting in uncontrolled stimulus intensity. At 0.9 MAC, the third stimulation induced more positive responses than the first stimulation, independent of the mode of stimulation used. CONCLUSIONS: The MAC of isoflurane in the Shetland ponies was lower than expected with considerable variability among individuals. Constant current surface electrode stimulations were the most repeatable. A summation over the sequence of three supramaximal stimulations was observed around 0.9 MAC. CLINICAL RELEVANCE: The possibility that Shetland ponies require less isoflurane than horses needs further investigation. Constant current surface-electrode stimulations were the most repeatable. Repetitive supramaximal stimuli may have evoked movements at isoflurane concentrations that provide immobility when single supramaximal stimulation was applied.

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The clinical demand for a device to monitor Blood Pressure (BP) in ambulatory scenarios with minimal use of inflation cuffs is increasing. Based on the so-called Pulse Wave Velocity (PWV) principle, this paper introduces and evaluates a novel concept of BP monitor that can be fully integrated within a chest sensor. After a preliminary calibration, the sensor provides non-occlusive beat-by-beat estimations of Mean Arterial Pressure (MAP) by measuring the Pulse Transit Time (PTT) of arterial pressure pulses travelling from the ascending aorta towards the subcutaneous vasculature of the chest. In a cohort of 15 healthy male subjects, a total of 462 simultaneous readings consisting of reference MAP and chest PTT were acquired. Each subject was recorded at three different days: D, D+3 and D+14. Overall, the implemented protocol induced MAP values to range from 80 ± 6 mmHg in baseline, to 107 ± 9 mmHg during isometric handgrip maneuvers. Agreement between reference and chest-sensor MAP values was tested by using intraclass correlation coefficient (ICC = 0.78) and Bland-Altman analysis (mean error = 0.7 mmHg, standard deviation = 5.1 mmHg). The cumulative percentage of MAP values provided by the chest sensor falling within a range of ±5 mmHg compared to reference MAP readings was of 70%, within ±10 mmHg was of 91%, and within ±15mmHg was of 98%. These results point at the fact that the chest sensor complies with the British Hypertension Society (BHS) requirements of Grade A BP monitors, when applied to MAP readings. Grade A performance was maintained even two weeks after having performed the initial subject-dependent calibration. In conclusion, this paper introduces a sensor and a calibration strategy to perform MAP measurements at the chest. The encouraging performance of the presented technique paves the way towards an ambulatory-compliant, continuous and non-occlusive BP monitoring system.

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This paper addresses an investigation with machine learning (ML) classification techniques to assist in the problem of flash flood now casting. We have been attempting to build a Wireless Sensor Network (WSN) to collect measurements from a river located in an urban area. The machine learning classification methods were investigated with the aim of allowing flash flood now casting, which in turn allows the WSN to give alerts to the local population. We have evaluated several types of ML taking account of the different now casting stages (i.e. Number of future time steps to forecast). We have also evaluated different data representation to be used as input of the ML techniques. The results show that different data representation can lead to results significantly better for different stages of now casting.