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- All Subjects: Biomedical Engineering
- Genre: Masters Thesis
Description
Single cell phenotypic heterogeneity studies reveal more information about the pathogenesis process than conventional bulk methods. Furthermore, investigation of the individual cellular response mechanism during rapid environmental changes can only be achieved at single cell level. By enabling the study of cellular morphology, a single cell three-dimensional (3D) imaging system can be used to diagnose fatal diseases, such as cancer, at an early stage. One proven method, CellCT, accomplishes 3D imaging by rotating a single cell around a fixed axis. However, some existing cell rotating mechanisms require either intricate microfabrication, and some fail to provide a suitable environment for living cells. This thesis develops a microvorterx chamber that allows living cells to be rotated by hydrodynamic alone while facilitating imaging access. In this thesis work, 1) the new chamber design was developed through numerical simulation. Simulations revealed that in order to form a microvortex in the side chamber, the ratio of the chamber opening to the channel width must be smaller than one. After comparing different chamber designs, the trapezoidal side chamber was selected because it demonstrated controllable circulation and met the imaging requirements. Microvortex properties were not sensitive to the chambers with interface angles ranging from 0.32 to 0.64. A similar trend was observed when chamber heights were larger than chamber opening. 2) Micro-particle image velocimetry was used to characterize microvortices and validate simulation results. Agreement between experimentation and simulation confirmed that numerical simulation was an effective method for chamber design. 3) Finally, cell rotation experiments were performed in the trapezoidal side chamber. The experimental results demonstrated cell rotational rates ranging from 12 to 29 rpm for regular cells. With a volumetric flow rate of 0.5 µL/s, an irregular cell rotated at a mean rate of 97 ± 3 rpm. Rotational rates can be changed by altering inlet flow rates.
ContributorsZhang, Wenjie (Author) / Frakes, David (Thesis advisor) / Meldrum, Deirdre (Thesis advisor) / Chao, Shih-hui (Committee member) / Wang, Xiao (Committee member) / Arizona State University (Publisher)
Created2011
Description
In recent years, the field of nanomedicine has progressed at an astonishing rate, particularly with respect to applications in cancer treatment and molecular imaging. Although organic systems have been the frontrunners, inorganic systems have also begun to show promise, especially those based upon silica and magnetic nanoparticles (NPs). Many of these systems are being designed for simultaneous therapeutic and diagnostic capabilities, thus coining the term, theranostics. A unique class of inorganic systems that shows great promise as theranostics is that of layered double hydroxides (LDH). By synthesis of a core/shell structures, e.g. a gold nanoparticle (NP) core and LDH shell, the multifunctional theranostic may be developed without a drastic increase in the structural complexity. To demonstrate initial proof-of-concept of a potential (inorganic) theranostic platform, a Au-core/LDH-shell nanovector has been synthesized and characterized. The LDH shell was heterogeneously nucleated and grown on the surface of silica coated gold NPs via a coprecipitation method. Polyethylene glycol (PEG) was introduced in the initial synthesis steps to improve crystallinity and colloidal stability. Additionally, during synthesis, fluorescein isothiocyanate (FITC) was intercalated into the interlayer spacing of the LDH. In contrast to the PEG stabilization, a post synthesis citric acid treatment was used as a method to control the size and short-term stability. The heterogeneous core-shell system was characterized with scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy (EDX), dynamic light scattering (DLS), and powder x-ray diffraction (PXRD). A preliminary in vitro study carried out with the assistance of Dr. Kaushal Rege's group at Arizona State University was to demonstrate the endocytosis capability of homogeneously-grown LDH NPs. The DLS measurements of the core-shell NPs indicated an average particle size of 212nm. The PXRD analysis showed that PEG greatly improved the crystallinity of the system while simultaneously preventing aggregation of the NPs. The preliminary in vitro fluorescence microscopy revealed a moderate uptake of homogeneous LDH NPs into the cells.
ContributorsRearick, Colton (Author) / Dey, Sandwip K (Thesis advisor) / Krause, Stephen (Committee member) / Ramakrishna, B (Committee member) / Arizona State University (Publisher)
Created2011
Description
In the search for chemical biosensors designed for patient-based physiological applications, non-invasive diagnostic approaches continue to have value. The work described in this thesis builds upon previous breath analysis studies. In particular, it seeks to assess the adsorptive mechanisms active in both acetone and ethanol biosensors designed for breath analysis. The thermoelectric biosensors under investigation were constructed using a thermopile for transduction and four different materials for biorecognition. The analytes, acetone and ethanol, were evaluated under dry-air and humidified-air conditions. The biosensor response to acetone concentration was found to be both repeatable and linear, while the sensor response to ethanol presence was also found to be repeatable. The different biorecognition materials produced discernible thermoelectric responses that were characteristic for each analyte. The sensor output data is presented in this report. Additionally, the results were evaluated against a mathematical model for further analysis. Ultimately, a thermoelectric biosensor based upon adsorption chemistry was developed and characterized. Additional work is needed to characterize the physicochemical action mechanism.
ContributorsWilson, Kimberly (Author) / Guilbeau, Eric (Thesis advisor) / Pizziconi, Vincent (Thesis advisor) / LaBelle, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2011
Description
In this thesis, I present a lab-on-a-chip (LOC) that can separate and detect Escherichia Coli (E. coli) in simulated urine samples for Urinary Tract Infection (UTI) diagnosis. The LOC consists of two (concentration and sensing) chambers connected in series and an integrated impedance detector. The two-chamber approach is designed to reduce the non-specific absorption of proteins, e.g. albumin, that potentially co-exist with E. coli in urine. I directly separate E. coli K-12 from a urine cocktail in a concentration chamber containing micro-sized magnetic beads (5 µm in diameter) conjugated with anti-E. coli antibodies. The immobilized E. coli are transferred to a sensing chamber for the impedance measurement. The measurement at the concentration chamber suffers from non-specific absorption of albumin on the gold electrode, which may lead to a false positive response. By contrast, the measured impedance at the sensing chamber shows ~60 kÙ impedance change between 6.4x104 and 6.4x105 CFU/mL, covering the threshold of UTI (105 CFU/mL). The sensitivity of the LOC for detecting E. coli is characterized to be at least 3.4x104 CFU/mL. I also characterized the LOC for different age groups and white blood cell spiked samples. These preliminary data show promising potential for application in portable LOC devices for UTI detection.
ContributorsKim, Sangpyeong (Author) / Chae, Junseok (Thesis advisor) / Phillips, Stephen M. (Committee member) / Blain Christen, Jennifer M. (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
Anticipatory planning of digit positions and forces is critical for successful dexterous object manipulation. Anticipatory (feedforward) planning bypasses the inherent delays in reflex responses and sensorimotor integration associated with reactive (feedback) control. It has been suggested that feedforward and feedback strategies can be distinguished based on the profile of grip and load force rates during the period between initial contact with the object and object lift. However, this has not been validated in tasks that do not constrain digit placement. The purposes of this thesis were (1) to validate the hypothesis that force rate profiles are indicative of the control strategy used for object manipulation and (2) to test this hypothesis by comparing manipulation tasks performed with and without digit placement constraints. The first objective comprised two studies. In the first study an additional light or heavy mass was added to the base of the object. In the second study a mass was added, altering the object's center of mass (CM) location. In each experiment digit force rates were calculated between the times of initial digit contact and object lift. Digit force rates were fit to a Gaussian bell curve and the goodness of fit was compared across predictable and unpredictable mass and CM conditions. For both experiments, a predictable object mass and CM elicited bell shaped force rate profiles, indicative of feedforward control. For the second objective, a comparison of performance between subjects who performed the grasp task with either constrained or unconstrained digit contact locations was conducted. When digit location was unconstrained and CM was predictable, force rates were well fit to a bell shaped curve. However, the goodness of fit of the force rate profiles to the bell shaped curve was weaker for the constrained than the unconstrained digit placement condition. These findings seem to indicate that brain can generate an appropriate feedforward control strategy even when digit placement is unconstrained and an infinite combination of digit placement and force solutions exists to lift the object successfully. Future work is needed that investigates the role digit positioning and tactile feedback has on anticipatory control of object manipulation.
ContributorsCooperhouse, Michael A (Author) / Santello, Marco (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2011
Description
Detecting anatomical structures, such as the carina, the pulmonary trunk and the aortic arch, is an important step in designing a CAD system of detection Pulmonary Embolism. The presented CAD system gets rid of the high-level prior defined knowledge to become a system which can easily extend to detect other anatomic structures. The system is based on a machine learning algorithm --- AdaBoost and a general feature --- Haar. This study emphasizes on off-line and on-line AdaBoost learning. And in on-line AdaBoost, the thesis further deals with extremely imbalanced condition. The thesis first reviews several knowledge-based detection methods, which are relied on human being's understanding of the relationship between anatomic structures. Then the thesis introduces a classic off-line AdaBoost learning. The thesis applies different cascading scheme, namely multi-exit cascading scheme. The comparison between the two methods will be provided and discussed. Both of the off-line AdaBoost methods have problems in memory usage and time consuming. Off-line AdaBoost methods need to store all the training samples and the dataset need to be set before training. The dataset cannot be enlarged dynamically. Different training dataset requires retraining the whole process. The retraining is very time consuming and even not realistic. To deal with the shortcomings of off-line learning, the study exploited on-line AdaBoost learning approach. The thesis proposed a novel pool based on-line method with Kalman filters and histogram to better represent the distribution of the samples' weight. Analysis of the performance, the stability and the computational complexity will be provided in the thesis. Furthermore, the original on-line AdaBoost performs badly in imbalanced conditions, which occur frequently in medical image processing. In image dataset, positive samples are limited and negative samples are countless. A novel Self-Adaptive Asymmetric On-line Boosting method is presented. The method utilized a new asymmetric loss criterion with self-adaptability according to the ratio of exposed positive and negative samples and it has an advanced rule to update sample's importance weight taking account of both classification result and sample's label. Compared to traditional on-line AdaBoost Learning method, the new method can achieve far more accuracy in imbalanced conditions.
ContributorsWu, Hong (Author) / Liang, Jianming (Thesis advisor) / Farin, Gerald (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2011
Description
In the past decade, research on the motor control side of neuroprosthetics has steadily gained momentum. However, modern research in prosthetic development supplements a focus on motor control with a concentration on sensory feedback. Simulating sensation is a central issue because without sensory capabilities, the sophistication of the most advanced motor control system fails to reach its full potential. This research is an effort toward the development of sensory feedback specifically for neuroprosthetic hands. The present aim of this work is to understand the processing and representation of cutaneous sensation by evaluating performance and neural activity in somatosensory cortex (SI) during a grasp task. A non-human primate (Macaca mulatta) was trained to reach out and grasp textured instrumented objects with a precision grip. Two different textures for the objects were used, 100% cotton cloth and 60-grade sandpaper, and the target object was presented at two different orientations. Of the 167 cells that were isolated for this experiment, only 42 were recorded while the subject executed a few blocks of successful trials for both textures. These latter cells were used in this study's statistical analysis. Of these, 37 units (88%) exhibited statistically significant task related activity. Twenty-two units (52%) exhibited statistically significant tuning to texture, and 16 units (38%) exhibited statistically significant tuning to posture. Ten of the cells (24%) exhibited statistically significant tuning to both texture and posture. These data suggest that single units in somatosensory cortex can encode multiple phenomena such as texture and posture. However, if this information is to be used to provide sensory feedback for a prosthesis, scientists must learn to further parse cortical activity to discover how to induce specific modalities of sensation. Future experiments should therefore be developed that probe more variables and that more systematically and comprehensively scan somatosensory cortex. This will allow researchers to seek out the existence or non-existence of cortical pockets reserved for certain modalities of sensation, which will be valuable in learning how to later provide appropriate sensory feedback for a prosthesis through cortical stimulation.
ContributorsNaufel, Stephanie (Author) / Helms Tillery, Stephen I (Thesis advisor) / Santos, Veronica J (Thesis advisor) / Buneo, Christopher A (Committee member) / Robert, Jason S (Committee member) / Arizona State University (Publisher)
Created2011
Description
Advancements in mobile technologies have significantly enhanced the capabilities of mobile devices to serve as powerful platforms for sensing, processing, and visualization. Surges in the sensing technology and the abundance of data have enabled the use of these portable devices for real-time data analysis and decision-making in digital signal processing (DSP) applications. Most of the current efforts in DSP education focus on building tools to facilitate understanding of the mathematical principles. However, there is a disconnect between real-world data processing problems and the material presented in a DSP course. Sophisticated mobile interfaces and apps can potentially play a crucial role in providing a hands-on-experience with modern DSP applications to students. In this work, a new paradigm of DSP learning is explored by building an interactive easy-to-use health monitoring application for use in DSP courses. This is motivated by the increasing commercial interest in employing mobile phones for real-time health monitoring tasks. The idea is to exploit the computational abilities of the Android platform to build m-Health modules with sensor interfaces. In particular, appropriate sensing modalities have been identified, and a suite of software functionalities have been developed. Within the existing framework of the AJDSP app, a graphical programming environment, interfaces to on-board and external sensor hardware have also been developed to acquire and process physiological data. The set of sensor signals that can be monitored include electrocardiogram (ECG), photoplethysmogram (PPG), accelerometer signal, and galvanic skin response (GSR). The proposed m-Health modules can be used to estimate parameters such as heart rate, oxygen saturation, step count, and heart rate variability. A set of laboratory exercises have been designed to demonstrate the use of these modules in DSP courses. The app was evaluated through several workshops involving graduate and undergraduate students in signal processing majors at Arizona State University. The usefulness of the software modules in enhancing student understanding of signals, sensors and DSP systems were analyzed. Student opinions about the app and the proposed m-health modules evidenced the merits of integrating tools for mobile sensing and processing in a DSP curriculum, and familiarizing students with challenges in modern data-driven applications.
ContributorsRajan, Deepta (Author) / Spanias, Andreas (Thesis advisor) / Frakes, David (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Functional magnetic resonance imaging (fMRI) has been widely used to measure the retinotopic organization of early visual cortex in the human brain. Previous studies have identified multiple visual field maps (VFMs) based on statistical analysis of fMRI signals, but the resulting geometry has not been fully characterized with mathematical models. This thesis explores using concepts from computational conformal geometry to create a custom software framework for examining and generating quantitative mathematical models for characterizing the geometry of early visual areas in the human brain. The software framework includes a graphical user interface built on top of a selected core conformal flattening algorithm and various software tools compiled specifically for processing and examining retinotopic data. Three conformal flattening algorithms were implemented and evaluated for speed and how well they preserve the conformal metric. All three algorithms performed well in preserving the conformal metric but the speed and stability of the algorithms varied. The software framework performed correctly on actual retinotopic data collected using the standard travelling-wave experiment. Preliminary analysis of the Beltrami coefficient for the early data set shows that selected regions of V1 that contain reasonably smooth eccentricity and polar angle gradients do show significant local conformality, warranting further investigation of this approach for analysis of early and higher visual cortex.
ContributorsTa, Duyan (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Wonka, Peter (Committee member) / Arizona State University (Publisher)
Created2013