Matching Items (93)
Description
Demand for biosensor research applications is growing steadily. According to a new report by Frost & Sullivan, the biosensor market is expected to reach $14.42 billion by 2016. Clinical diagnostic applications continue to be the largest market for biosensors, and this demand is likely to continue through 2016 and beyond. Biosensor technology for use in clinical diagnostics, however, requires translational research that moves bench science and theoretical knowledge toward marketable products. Despite the high volume of academic research to date, only a handful of biomedical devices have become viable commercial applications. Academic research must increase its focus on practical uses for biosensors. This dissertation is an example of this increased focus, and discusses work to advance microfluidic-based protein biosensor technologies for practical use in clinical diagnostics. Four areas of work are discussed: The first involved work to develop reusable/reconfigurable biosensors that are useful in applications like biochemical science and analytical chemistry that require detailed sensor calibration. This work resulted in a prototype sensor and an in-situ electrochemical surface regeneration technique that can be used to produce microfluidic-based reusable biosensors. The second area of work looked at non-specific adsorption (NSA) of biomolecules, which is a persistent challenge in conventional microfluidic biosensors. The results of this work produced design methods that reduce the NSA. The third area of work involved a novel microfluidic sensing platform that was designed to detect target biomarkers using competitive protein adsorption. This technique uses physical adsorption of proteins to a surface rather than complex and time-consuming immobilization procedures. This method enabled us to selectively detect a thyroid cancer biomarker, thyroglobulin, in a controlled-proteins cocktail and a cardiovascular biomarker, fibrinogen, in undiluted human serum. The fourth area of work involved expanding the technique to produce a unique protein identification method; Pattern-recognition. A sample mixture of proteins generates a distinctive composite pattern upon interaction with a sensing platform consisting of multiple surfaces whereby each surface consists of a distinct type of protein pre-adsorbed on the surface. The utility of the "pattern-recognition" sensing mechanism was then verified via recognition of a particular biomarker, C-reactive protein, in the cocktail sample mixture.
ContributorsChoi, Seokheun (Author) / Chae, Junseok (Thesis advisor) / Tao, Nongjian (Committee member) / Yu, Hongyu (Committee member) / Forzani, Erica (Committee member) / Arizona State University (Publisher)
Created2011
Description
Sensing and controlling current flow is a fundamental requirement for many electronic systems, including power management (DC-DC converters and LDOs), battery chargers, electric vehicles, solenoid positioning, motor control, and power monitoring. Current Shunt Monitor (CSM) systems have various applications for precise current monitoring of those aforementioned applications. CSMs enable current measurement across an external sense resistor (RS) in series to current flow. Two different types of CSMs designed and characterized in this paper. First design used direct current reading method and the other design used indirect current reading method. Proposed CSM systems can sense power supply current ranging from 1mA to 200mA for the direct current reading topology and from 1mA to 500mA for the indirect current reading topology across a typical board Cu-trace resistance of 1 ohm with less than 10 µV input-referred offset, 0.3 µV/°C offset drift and 0.1% accuracy for both topologies. Proposed systems avoid using a costly zero-temperature coefficient (TC) sense resistor that is normally used in typical CSM systems. Instead, both of the designs used existing Cu-trace on the printed circuit board (PCB) in place of the costly resistor. The systems use chopper stabilization at the front-end amplifier signal path to suppress input-referred offset down to less than 10 µV. Switching current-mode (SI) FIR filtering technique is used at the instrumentation amplifier output to filter out the chopping ripple caused by input offset and flicker noise by averaging half of the phase 1 signal and the other half of the phase 2 signal. In addition, residual offset mainly caused by clock feed-through and charge injection of the chopper switches at the chopping frequency and its multiple frequencies notched out by the since response of the SI-FIR filter. A frequency domain Sigma Delta ADC which is used for the indirect current reading type design enables a digital interface to processor applications with minimally added circuitries to build a simple 1st order Sigma Delta ADC. The CSMs are fabricated on a 0.7µm CMOS process with 3 levels of metal, with maximum Vds tolerance of 8V and operates across a common mode range of 0 to 26V for the direct current reading type and of 0 to 30V for the indirect current reading type achieving less than 10nV/sqrtHz of flicker noise at 100 Hz for both approaches. By using a semi-digital SI-FIR filter, residual chopper offset is suppressed down to 0.5mVpp from a baseline of 8mVpp, which is equivalent to 25dB suppression.
ContributorsYeom, Hyunsoo (Author) / Bakkaloglu, Bertan (Thesis advisor) / Kiaei, Sayfe (Committee member) / Ozev, Sule (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2011
Description
Negative bias temperature instability (NBTI) and channel hot carrier (CHC) are important reliability issues impacting analog circuit performance and lifetime. Compact reliability models and efficient simulation methods are essential for circuit level reliability prediction. This work proposes a set of compact models of NBTI and CHC effects for analog and mixed-signal circuit, and a direct prediction method which is different from conventional simulation methods. This method is applied in circuit benchmarks and evaluated. This work helps with improving efficiency and accuracy of circuit aging prediction.
ContributorsZheng, Rui (Author) / Cao, Yu (Thesis advisor) / Yu, Hongyu (Committee member) / Bakkaloglu, Bertan (Committee member) / Arizona State University (Publisher)
Created2011
Description
There is increasing interest in the medical and behavioral health communities towards developing effective strategies for the treatment of chronic diseases. Among these lie adaptive interventions, which consider adjusting treatment dosages over time based on participant response. Control engineering offers a broad-based solution framework for optimizing the effectiveness of such interventions. In this thesis, an approach is proposed to develop dynamical models and subsequently, hybrid model predictive control schemes for assigning optimal dosages of naltrexone, an opioid antagonist, as treatment for a chronic pain condition known as fibromyalgia. System identification techniques are employed to model the dynamics from the daily diary reports completed by participants of a blind naltrexone intervention trial. These self-reports include assessments of outcomes of interest (e.g., general pain symptoms, sleep quality) and additional external variables (disturbances) that affect these outcomes (e.g., stress, anxiety, and mood). Using prediction-error methods, a multi-input model describing the effect of drug, placebo and other disturbances on outcomes of interest is developed. This discrete time model is approximated by a continuous second order model with zero, which was found to be adequate to capture the dynamics of this intervention. Data from 40 participants in two clinical trials were analyzed and participants were classified as responders and non-responders based on the models obtained from system identification. The dynamical models can be used by a model predictive controller for automated dosage selection of naltrexone using feedback/feedforward control actions in the presence of external disturbances. The clinical requirement for categorical (i.e., discrete-valued) drug dosage levels creates a need for hybrid model predictive control (HMPC). The controller features a multiple degree-of-freedom formulation that enables the user to adjust the speed of setpoint tracking, measured disturbance rejection and unmeasured disturbance rejection independently in the closed loop system. The nominal and robust performance of the proposed control scheme is examined via simulation using system identification models from a representative participant in the naltrexone intervention trial. The controller evaluation described in this thesis gives credibility to the promise and applicability of control engineering principles for optimizing adaptive interventions.
ContributorsDeśapāṇḍe, Sunīla (Author) / Rivera, Daniel E. (Thesis advisor) / Si, Jennie (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2011
Description
The past two decades have been monumental in the advancement of microchips designed for a diverse range of medical applications and bio-analysis. Owing to the remarkable progress in micro-fabrication technology, complex chemical and electro-mechanical features can now be integrated into chip-scale devices for use in biosensing and physiological measurements. Some of these devices have made enormous contributions in the study of complex biochemical processes occurring at the molecular and cellular levels while others overcame the challenges of replicating various functions of human organs as implant systems. This thesis presents test data and analysis of two such systems. First, an ISFET based pH sensor is characterized for its performance in a continuous pH monitoring application. Many of the basic properties of ISFETs including I-V characteristics, pH sensitivity and more importantly, its long term drift behavior have been investigated. A new theory based on frequent switching of electric field across the gate oxide to decrease the rate of current drift has been successfully implemented with the help of an automated data acquisition and switching system. The system was further tested for a range of duty cycles in order to accurately determine the minimum length of time required to fully reset the drift. Second, a microfluidic based vestibular implant system was tested for its underlying characteristics as a light sensor. A computer controlled tilt platform was then implemented to further test its sensitivity to inclinations and thus it‟s more important role as a tilt sensor. The sensor operates through means of optoelectronics and relies on the signals generated from photodiode arrays as a result of light being incident on them. ISFET results show a significant drop in the overall drift and good linear characteristics. The drift was seen to reset at less than an hour. The photodiodes show ideal I-V comparison between photoconductive and photovoltaic modes of operation with maximum responsivity at 400nm and a shunt resistance of 394 MΩ. Additionally, post-processing of the tilt sensor to incorporate the sensing fluids is outlined. Based on several test and fabrication results, a possible method of sealing the open cavity of the chip using a UV curable epoxy has been discussed.
ContributorsMamun, Samiha (Author) / Christen, Jennifer Blain (Thesis advisor) / Goryll, Michael (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis investigated two different thermal flow sensors for intravascular shear stress analysis. They were based on heat transfer principle, which heat convection from the resistively heated element to the flowing fluid was measured as a function of the changes in voltage. For both sensors, the resistively heated elements were made of Ti/Pt strips with the thickness 0.12 µm and 0.02 µm. The resistance of the sensing element was measured at approximately 1.6-1.7 kohms;. A linear relation between the resistance and temperature was established over the temperature ranging from 22 degree Celsius to 80 degree Celsius and the temperature coefficient of resistance (TCR) was at approximately 0.12 %/degree Celsius. The first thermal flow sensor was one-dimensional (1-D) flexible shear stress sensor. The structure was sensing element sandwiched by a biocompatible polymer "poly-para-xylylene", also known as Parylene, which provided both insulation of electrodes and flexibility of the sensors. A constant-temperature (CT) circuit was designed as the read out circuit based on 0.6 µm CMOS (Complementary metal-oxide-semiconductor) process. The 1-D shear stress sensor suffered from a large measurement error. Because when the sensor was inserted into blood vessels, it was impossible to mount the sensor to the wall as calibrated in micro fluidic channels. According to the previous simulation work, the shear stress was varying and the sensor itself changed the shear stress distribution. We proposed a three-dimensional (3-D) thermal flow sensor, with three-axis of sensing elements integrated in one sensor. It was in the similar shape as a hexagonal prism with diagonal of 1000 µm. On the top of the sensor, there were five bond pads for external wires over 500 µm thick silicon substrate. In each nonadjacent side surface, there was a bended parylene branch with one sensing element. Based on the unique 3-D structure, the sensor was able to obtain data along three axes. With computational fluid dynamics (CFD) model, it is possible to locate the sensor in the blood vessels and give us a better understanding of shear stress distribution in the presence of time-varying component of blood flow and realize more accurate assessment of intravascular convective heat transfer.
ContributorsTang, Rui (Author) / Yu, Hongyu (Thesis advisor) / Jiang, Hanqing (Committee member) / Pan, George (Committee member) / Arizona State University (Publisher)
Created2011
Description
Due to restructuring and open access to the transmission system, modern electric power systems are being operated closer to their operational limits. Additionally, the secure operational limits of modern power systems have become increasingly difficult to evaluate as the scale of the network and the number of transactions between utilities increase. To account for these challenges associated with the rapid expansion of electric power systems, dynamic equivalents have been widely applied for the purpose of reducing the computational effort of simulation-based transient security assessment. Dynamic equivalents are commonly developed using a coherency-based approach in which a retained area and an external area are first demarcated. Then the coherent generators in the external area are aggregated and replaced by equivalenced models, followed by network reduction and load aggregation. In this process, an improperly defined retained area can result in detrimental impacts on the effectiveness of the equivalents in preserving the dynamic characteristics of the original unreduced system. In this dissertation, a comprehensive approach has been proposed to determine an appropriate retained area boundary by including the critical generators in the external area that are tightly coupled with the initial retained area. Further-more, a systematic approach has also been investigated to efficiently predict the variation in generator slow coherency behavior when the system operating condition is subject to change. Based on this determination, the critical generators in the external area that are tightly coherent with the generators in the initial retained area are retained, resulting in a new retained area boundary. Finally, a novel hybrid dynamic equivalent, consisting of both a coherency-based equivalent and an artificial neural network (ANN)-based equivalent, has been proposed and analyzed. The ANN-based equivalent complements the coherency-based equivalent at all the retained area boundary buses, and it is designed to compensate for the discrepancy between the full system and the conventional coherency-based equivalent. The approaches developed have been validated on a large portion of the Western Electricity Coordinating Council (WECC) system and on a test case including a significant portion of the eastern interconnection.
ContributorsMa, Feng (Author) / Vittal, Vijay (Thesis advisor) / Tylavsky, Daniel (Committee member) / Heydt, Gerald (Committee member) / Si, Jennie (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2011
Description
Proportional-Integral-Derivative (PID) controllers are a versatile category of controllers that are commonly used in the industry as control systems due to the ease of their implementation and low cost. One problem that continues to intrigue control designers is the matter of finding a good combination of the three parameters - P, I and D of these controllers so that system stability and optimum performance is achieved. Also, a certain amount of robustness to the process is expected from the PID controllers. In the past, many different methods for tuning PID parameters have been developed. Some notable techniques are the Ziegler-Nichols, Cohen-Coon, Astrom methods etc. For all these techniques, a simple limitation remained with the fact that for a particular system, there can be only one set of tuned parameters; i.e. there are no degrees of freedom involved to readjust the parameters for a given system to achieve, for instance, higher bandwidth. Another limitation in most cases is where a controller is designed in continuous time then converted into discrete-time for computer implementation. The drawback of this method is that some robustness due to phase and gain margin is lost in the process. In this work a method of tuning PID controllers using a loop-shaping approach has been developed where the bandwidth of the system can be chosen within an acceptable range. The loop-shaping is done against a Glover-McFarlane type ℋ∞ controller which is widely accepted as a robust control design method. The numerical computations are carried out entirely in discrete-time so there is no loss of robustness due to conversion and approximations near Nyquist frequencies. Some extra degrees of freedom owing to choice of bandwidth and capability of choosing loop-shapes are also involved and are discussed in detail. Finally, comparisons of this method against existing techniques for tuning PID controllers both in continuous and in discrete-time are shown. The results tell us that our design performs well for loop-shapes that are achievable through a PID controller.
ContributorsShafique, Md. Ashfaque Bin (Author) / Tsakalis, Konstantinos S. (Thesis advisor) / Rodriguez, Armando A. (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2011
Description
This study focuses on state estimation of nonlinear discrete time systems with constraints. Physical processes have inherent in them, constraints on inputs, outputs, states and disturbances. These constraints can provide additional information to the estimator in estimating states from the measured output. Recursive filters such as Kalman Filters or Extended Kalman Filters are commonly used in state estimation; however, they do not allow inclusion of constraints in their formulation. On the other hand, computational complexity of full information estimation (using all measurements) grows with iteration and becomes intractable. One way of formulating the recursive state estimation problem with constraints is the Moving Horizon Estimation (MHE) approximation. Estimates of states are calculated from the solution of a constrained optimization problem of fixed size. Detailed formulation of this strategy is studied and properties of this estimation algorithm are discussed in this work. The problem with the MHE formulation is solving an optimization problem in each iteration which is computationally intensive. State estimation with constraints can be formulated as Extended Kalman Filter (EKF) with a projection applied to estimates. The states are estimated from the measurements using standard Extended Kalman Filter (EKF) algorithm and the estimated states are projected on to a constrained set. Detailed formulation of this estimation strategy is studied and the properties associated with this algorithm are discussed. Both these state estimation strategies (MHE and EKF with projection) are tested with examples from the literature. The average estimation time and the sum of square estimation error are used to compare performance of these estimators. Results of the case studies are analyzed and trade-offs are discussed.
ContributorsJoshi, Rakesh (Author) / Tsakalis, Konstantinos (Thesis advisor) / Rodriguez, Armando (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2013
Description
This thesis discusses control and obstacle avoidance for non-holonomic differential drive mobile vehicles. The two important behaviors for the vehicle can be defined as go to goal and obstacle avoidance behavior. This thesis discusses both behaviors in detail. Go to goal behavior is the ability of the mobile vehicle to go from one particular co-ordinate to another. Cruise control, cartesian and posture stabilization problems are discussed as the part of this behavior. Control strategies used for the above three problems are explained in the thesis. Matlab simulations are presented to verify these controllers. Obstacle avoidance behavior ensures that the vehicle doesn't hit object in its path while going towards the goal. Three different techniques for obstacle avoidance which are useful for different kind of obstacles are described in the thesis. Matlab simulations are presented to show and discuss the three techniques. The controls discussed for the cartesian and posture stabilization were implemented on a low cost miniature vehicle to verify the results practically. The vehicle is described in the thesis in detail. The practical results are compared with the simulations. Hardware and matlab codes have been provided as a reference for the reader.
ContributorsChopra, Dhruv (Author) / Rodriguez, Armando A (Thesis advisor) / Tsakalis, Konstantinos (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2013