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Description
Statistical process control (SPC) and predictive analytics have been used in industrial manufacturing and design, but up until now have not been applied to threshold data of vital sign monitoring in remote care settings. In this study of 20 elders with COPD and/or CHF, extended months of peak flow monitoring

Statistical process control (SPC) and predictive analytics have been used in industrial manufacturing and design, but up until now have not been applied to threshold data of vital sign monitoring in remote care settings. In this study of 20 elders with COPD and/or CHF, extended months of peak flow monitoring (FEV1) using telemedicine are examined to determine when an earlier or later clinical intervention may have been advised. This study demonstrated that SPC may bring less than a 2.0% increase in clinician workload while providing more robust statistically-derived thresholds than clinician-derived thresholds. Using a random K-fold model, FEV1 output was predictably validated to .80 Generalized R-square, demonstrating the adequate learning of a threshold classifier. Disease severity also impacted the model. Forecasting future FEV1 data points is possible with a complex ARIMA (45, 0, 49), but variation and sources of error require tight control. Validation was above average and encouraging for clinician acceptance. These statistical algorithms provide for the patient's own data to drive reduction in variability and, potentially increase clinician efficiency, improve patient outcome, and cost burden to the health care ecosystem.
ContributorsFralick, Celeste (Author) / Muthuswamy, Jitendran (Thesis advisor) / O'Shea, Terrance (Thesis advisor) / LaBelle, Jeffrey (Committee member) / Pizziconi, Vincent (Committee member) / Shea, Kimberly (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Image resolution limits the extent to which zooming enhances clarity, restricts the size digital photographs can be printed at, and, in the context of medical images, can prevent a diagnosis. Interpolation is the supplementing of known data with estimated values based on a function or model involving some or all

Image resolution limits the extent to which zooming enhances clarity, restricts the size digital photographs can be printed at, and, in the context of medical images, can prevent a diagnosis. Interpolation is the supplementing of known data with estimated values based on a function or model involving some or all of the known samples. The selection of the contributing data points and the specifics of how they are used to define the interpolated values influences how effectively the interpolation algorithm is able to estimate the underlying, continuous signal. The main contributions of this dissertation are three fold: 1) Reframing edge-directed interpolation of a single image as an intensity-based registration problem. 2) Providing an analytical framework for intensity-based registration using control grid constraints. 3) Quantitative assessment of the new, single-image enlargement algorithm based on analytical intensity-based registration. In addition to single image resizing, the new methods and analytical approaches were extended to address a wide range of applications including volumetric (multi-slice) image interpolation, video deinterlacing, motion detection, and atmospheric distortion correction. Overall, the new approaches generate results that more accurately reflect the underlying signals than less computationally demanding approaches and with lower processing requirements and fewer restrictions than methods with comparable accuracy.
ContributorsZwart, Christine M. (Author) / Frakes, David H (Thesis advisor) / Karam, Lina (Committee member) / Kodibagkar, Vikram (Committee member) / Spanias, Andreas (Committee member) / Towe, Bruce (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Alzheimer's disease (AD) is the leading neurodegenerative disease, affecting roughly 8% of people 65 years of age or older. There exists an imperative need to develop a non-invasive test for the earlier detection of AD. The use of biomarkers is a promising option that examines the toxic mechanisms and metabolic

Alzheimer's disease (AD) is the leading neurodegenerative disease, affecting roughly 8% of people 65 years of age or older. There exists an imperative need to develop a non-invasive test for the earlier detection of AD. The use of biomarkers is a promising option that examines the toxic mechanisms and metabolic pathways that cause Alzheimer's disease, eventually leading to an early diagnostic method. This thesis presents the use of oligomeric beta-amyloid as a biomarker to detect Alzheimer's disease via a specialized enzyme-linked protein assay. Specifically, this paper details the optimization and development of a novel phage capture enzyme-linked immunosorbent assay (ELISA) that can detect the relative quantity of beta-amyloid oligomers in samples from a mouse model of AD. The objective of this thesis was to optimize a phage capture ELISA using the A4 single-chain variable fragment (scFv) to quantify the amount of beta-amyloid oligomers in various mice samples. A4 selectively recognizes a toxic oligomeric form of beta-amyloid. The level of A4-reactive oligomeric beta-amyloid was measured in triplicate in homogenized mouse brain tissue samples from eight transgenic (TG) and eight nontransgenic (NTG) animals aged five, nine, and thirteen months. There was a significant difference (p < 0.0005) between the five month TG and NTG mice. A decrease in beta-amyloid levels with the aging of the TG mice suggested that the beta-amyloid oligomers may be aggregating to form beta-amyloid fibrils. Conversely, the quantity of beta-amyloid increased with the aging of the NTG mice. This indicated that beta-amyloid oligomers may develop with normal aging.
ContributorsBrownlee, Taylor (Author) / Sierks, Michael (Thesis advisor) / Williams, Stephanie (Committee member) / Xin, Wei (Committee member) / Arizona State University (Publisher)
Created2013
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Description
In order to successfully implement a neural prosthetic system, it is necessary to understand the control of limb movements and the representation of body position in the nervous system. As this development process continues, it is becoming increasingly important to understand the way multiple sensory modalities are used in limb

In order to successfully implement a neural prosthetic system, it is necessary to understand the control of limb movements and the representation of body position in the nervous system. As this development process continues, it is becoming increasingly important to understand the way multiple sensory modalities are used in limb representation. In a previous study, Shi et al. (2013) examined the multimodal basis of limb position in the superior parietal lobule (SPL) as monkeys reached to and held their arm at various target locations in a frontal plane. Visual feedback was withheld in half the trials, though non-visual (i.e. somatic) feedback was available in all trials. Previous analysis showed that some of the neurons were tuned to limb position and that some neurons had their response modulated by the presence or absence of visual feedback. This modulation manifested in decreases in firing rate variability in the vision condition as compared to nonvision. The decreases in firing rate variability, as shown through decreases in both the Fano factor of spike counts and the coefficient of variation of the inter-spike intervals, suggested that changes were taking place in both trial-by-trial and intra-trial variability. I sought to further probe the source of the change in intra-trial variability through spectral analysis. It was hypothesized that the presence of temporal structure in the vision condition would account for a regularity in firing that would have decreased intra-trial variability. While no peaks were apparent in the spectra, differences in spectral power between visual conditions were found. These differences are suggestive of unique temporal spiking patterns at the individual neuron level that may be influential at the population level.
ContributorsDyson, Keith (Author) / Buneo, Christopher A (Thesis advisor) / Helms-Tillery, Stephen I (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This research is focused on two separate but related topics. The first uses an electroencephalographic (EEG) brain-computer interface (BCI) to explore the phenomenon of motor learning transfer. The second takes a closer look at the EEG-BCI itself and tests an alternate way of mapping EEG signals into machine commands. We

This research is focused on two separate but related topics. The first uses an electroencephalographic (EEG) brain-computer interface (BCI) to explore the phenomenon of motor learning transfer. The second takes a closer look at the EEG-BCI itself and tests an alternate way of mapping EEG signals into machine commands. We test whether motor learning transfer is more related to use of shared neural structures between imagery and motor execution or to more generalized cognitive factors. Using an EEG-BCI, we train one group of participants to control the movements of a cursor using embodied motor imagery. A second group is trained to control the cursor using abstract motor imagery. A third control group practices moving the cursor using an arm and finger on a touch screen. We hypothesized that if motor learning transfer is related to the use of shared neural structures then the embodied motor imagery group would show more learning transfer than the abstract imaging group. If, on the other hand, motor learning transfer results from more general cognitive processes, then the abstract motor imagery group should also demonstrate motor learning transfer to the manual performance of the same task. Our findings support that motor learning transfer is due to the use of shared neural structures between imaging and motor execution of a task. The abstract group showed no motor learning transfer despite being better at EEG-BCI control than the embodied group. The fact that more participants were able to learn EEG-BCI control using abstract imagery suggests that abstract imagery may be more suitable for EEG-BCIs for some disabilities, while embodied imagery may be more suitable for others. In Part 2, EEG data collected in the above experiment was used to train an artificial neural network (ANN) to map EEG signals to machine commands. We found that our open-source ANN using spectrograms generated from SFFTs is fundamentally different and in some ways superior to Emotiv's proprietary method. Our use of novel combinations of existing technologies along with abstract and embodied imagery facilitates adaptive customization of EEG-BCI control to meet needs of individual users.
Contributorsda Silva, Flavio J. K (Author) / Mcbeath, Michael K (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Presson, Clark (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2013
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Description
As schools across Arizona worked to meet NCLB's AYP requirement in 2010-2011, they were also labeled and sanctioned by AZ Learns. This phenomenological study focused on six effective high school principals in two Arizona school districts to ascertain how accountability policies impacted the principals' job responsibilities, autonomy, and ability to

As schools across Arizona worked to meet NCLB's AYP requirement in 2010-2011, they were also labeled and sanctioned by AZ Learns. This phenomenological study focused on six effective high school principals in two Arizona school districts to ascertain how accountability policies impacted the principals' job responsibilities, autonomy, and ability to pursue social justice on their campuses. Interviews were conducted in three phases: superintendents, three principals from the superintendents' recommendations of effective school leaders, and three teachers from each school. In addition to analysis of individual principal leadership patterns, comparisons were made across districts, and from school to school within the same district. The goal of the study was to determine if and how principals were able to accomplish their goals for their school. The principals' leadership styles were examined through a Vortex Leadership Framework that posited principals at the center of a vortex of varying leadership roles, interests, and external forces, including accountability, autonomy, and limited resources. Key findings included (a) high school principals' responsibilities now include selling change to their staff, (b) principals' accountability is limited more by district constraints than by state or federal accountability, (c) principals must contend with rigid one-size fits all accountability standards that do not always meet the needs of their students, and (d) principals' autonomy is tied to their resources, including funding for staffing and programs.
ContributorsBatsell, Holly (Author) / Powers, Jeanne M. (Thesis advisor) / Mccarty, Teresa (Committee member) / Davey, Lynn (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The purpose of the study is to explore the identity development and organizational culture of a student organization, the National Association of Latino Fraternal Organizations council (NALFO) by implementing a community of practice approach at a large, public university in southwestern United States. The objective is to construct a sustainable

The purpose of the study is to explore the identity development and organizational culture of a student organization, the National Association of Latino Fraternal Organizations council (NALFO) by implementing a community of practice approach at a large, public university in southwestern United States. The objective is to construct a sustainable camaraderie among the existing Latino fraternal organizations at the university to influence leadership development, work toward a common vision, and a cohesive and systematic approach to collaboration, consequently transforming organizational culture. This study investigates the factors that contribute to and/or inhibit increased communication and collaboration and to describe the experiences of Latino fraternal members who are purposefully engaged in a community of practice. There are 57 fraternal organizations in five umbrella councils at the university, including predominately Caucasian, historically African American, Latino, and Multicultural groups, whose platforms are commonly leadership, scholarship, and philanthropy. This action research examines the experiences of six NALFO members individually and working as a community with the guidance of a mentor (the researcher). The researcher employs use of an anonymous initial and post electronic survey, a participant personal statement, an intentional and purposeful community of practice, a semi-structured individual interview, and focus groups to collect data. Findings suggest that length of membership and fraternal experience influence participant responses; however, the themes remain consistent. Building relationships, perception (by members and outsiders), identity development, organizational management, and challenging perspectives (from outside influences) are factors that influence the organizational culture of the organization. On the post electronic survey all participants indicate that the implementation of an intentional community of practice can benefit the organization by encouraging participation and increasing communication. While participants suggest activities for encouraging member engagement, they determine that actual participation would be dependent on individual motivation.
ContributorsHeredia, Anna-Maria (Author) / Rund, James (Thesis advisor) / Calleroz White, Mistalene (Thesis advisor) / Corey, Frederick (Committee member) / Arizona State University (Publisher)
Created2013
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Description
In this mixed-methods study, I examined the relationship between professional development based on the Common Core State Standards for Mathematics and teacher knowledge, classroom practice, and student learning. Participants were randomly assigned to experimental and control groups. The 50-hour professional development treatment was administered to the treatment group during one

In this mixed-methods study, I examined the relationship between professional development based on the Common Core State Standards for Mathematics and teacher knowledge, classroom practice, and student learning. Participants were randomly assigned to experimental and control groups. The 50-hour professional development treatment was administered to the treatment group during one semester, and then a follow-up replication treatment was administered to the control group during the subsequent semester. Results revealed significant differences in teacher knowledge as a result of the treatment using two instruments. The Learning Mathematics for Teaching scales were used to detect changes in mathematical knowledge for teaching, and an online sorting task was used to detect changes in teachers' knowledge of their standards. Results also indicated differences in classroom practice between pairs of matched teachers selected to participate in classroom observations and interviews. No statistical difference was detected between the groups' student assessment scores using the district's benchmark assessment system. This efficacy study contributes to the literature in two ways. First, it provides an evidence base for a professional development model designed to promote effective implementation of the Common Core State Standards for Mathematics. Second, it addresses ways to impact and measure teachers' knowledge of curriculum in addition to their mathematical content knowledge. The treatment was designed to focus on knowledge of curriculum, but it also successfully impacted teachers' specialized content knowledge, knowledge of content and students, and knowledge of content and teaching.
ContributorsRimbey, Kimberly A (Author) / Middleton, James A. (Thesis advisor) / Sloane, Finbarr (Committee member) / Atkinson, Robert K (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Coronary heart disease (CHD) is the most prevalent cause of death worldwide. Atherosclerosis which is the condition of plaque buildup on the inside of the coronary artery wall is the main cause of CHD. Rupture of unstable atherosclerotic coronary plaque is known to be the cause of acute coronary syndrome.

Coronary heart disease (CHD) is the most prevalent cause of death worldwide. Atherosclerosis which is the condition of plaque buildup on the inside of the coronary artery wall is the main cause of CHD. Rupture of unstable atherosclerotic coronary plaque is known to be the cause of acute coronary syndrome. The composition of plaque is important for detection of plaque vulnerability. Due to prognostic importance of early stage identification, non-invasive assessment of plaque characterization is necessary. Computed tomography (CT) has emerged as a non-invasive alternative to coronary angiography. Recently, dual energy CT (DECT) coronary angiography has been performed clinically. DECT scanners use two different X-ray energies in order to determine the energy dependency of tissue attenuation values for each voxel. They generate virtual monochromatic energy images, as well as material basis pair images. The characterization of plaque components by DECT is still an active research topic since overlap between the CT attenuations measured in plaque components and contrast material shows that the single mean density might not be an appropriate measure for characterization. This dissertation proposes feature extraction, feature selection and learning strategies for supervised characterization of coronary atherosclerotic plaques. In my first study, I proposed an approach for calcium quantification in contrast-enhanced examinations of the coronary arteries, potentially eliminating the need for an extra non-contrast X-ray acquisition. The ambiguity of separation of calcium from contrast material was solved by using virtual non-contrast images. Additional attenuation data provided by DECT provides valuable information for separation of lipid from fibrous plaque since the change of their attenuation as the energy level changes is different. My second study proposed these as the input to supervised learners for a more precise classification of lipid and fibrous plaques. My last study aimed at automatic segmentation of coronary arteries characterizing plaque components and lumen on contrast enhanced monochromatic X-ray images. This required extraction of features from regions of interests. This study proposed feature extraction strategies and selection of important ones. The results show that supervised learning on the proposed features provides promising results for automatic characterization of coronary atherosclerotic plaques by DECT.
ContributorsYamak, Didem (Author) / Akay, Metin (Thesis advisor) / Muthuswamy, Jit (Committee member) / Akay, Yasemin (Committee member) / Pavlicek, William (Committee member) / Vernon, Brent (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Controlled release formulations for local, in vivo drug delivery are of growing interest to device manufacturers, research scientists, and clinicians; however, most research characterizing controlled release formulations occurs in vitro because the spatial and temporal distribution of drug delivery is difficult to measure in vivo. In this work, in vivo

Controlled release formulations for local, in vivo drug delivery are of growing interest to device manufacturers, research scientists, and clinicians; however, most research characterizing controlled release formulations occurs in vitro because the spatial and temporal distribution of drug delivery is difficult to measure in vivo. In this work, in vivo magnetic resonance imaging (MRI) of local drug delivery is performed to visualize and quantify the time resolved distribution of MRI contrast agents. I find it is possible to visualize contrast agent distributions in near real time from local delivery vehicles using MRI. Three dimensional T1 maps are processed to produce in vivo concentration maps of contrast agent for individual animal models. The method for obtaining concentration maps is analyzed to estimate errors introduced at various steps in the process. The method is used to evaluate different controlled release vehicles, vehicle placement, and type of surgical wound in rabbits as a model for antimicrobial delivery to orthopaedic infection sites. I are able to see differences between all these factors; however, all images show that contrast agent remains fairly local to the wound site and do not distribute to tissues far from the implant in therapeutic concentrations. I also produce a mathematical model that investigates important mechanisms in the transport of antimicrobials in a wound environment. It is determined from both the images and the mathematical model that antimicrobial distribution in an orthopaedic wounds is dependent on both diffusive and convective mechanisms. Furthermore, I began development of MRI visible therapeutic agents to examine active drug distributions. I hypothesize that this work can be developed into a non-invasive, patient specific, clinical tool to evaluate the success of interventional procedures using local drug delivery vehicles.
ContributorsGiers, Morgan (Author) / Caplan, Michael R (Thesis advisor) / Massia, Stephen P (Committee member) / Frakes, David (Committee member) / McLaren, Alex C. (Committee member) / Vernon, Brent L (Committee member) / Arizona State University (Publisher)
Created2013