Matching Items (8)
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- All Subjects: medicine
- Creators: Branaghan, Russell
- Creators: Pizziconi, Vincent
- Creators: Chiou, Erin
Description
The objective of this research is to develop a biocompatible scaffold based on dextran and poly acrylic acid (PAA) with the potential to be used for soft tissue repair. In this thesis, physical and chemical properties of the scaffold were investigated. The scaffolds were made using electrospinning and cross-linked under high temperature. After heat treatment, Scanning Electron Microscope (SEM) was used to observe the structures of these scaffolds. Fourier transform infrared spectroscopy (FTIR) was used to measure the cross-linking level of scaffold samples given different times of heat treatment by detecting and comparing the newly formed ester bonds. Single-walled carbon nanotubes (SWCNT) were added to enhance the mechanical properties of dextran-PAA scaffolds. Attachment of NIH-3T3 fibroblast cells to the scaffold and the response upon implantation into rabbit vaginal tissue were also evaluated to investigate the performance of SWCNT dextran-PAA scaffold. SEM was then used to characterize morphology of fibroblast cells and rabbit tissues. The results suggest that SWCNT could enhance cell attachment, distribution and spreading performance of dextran-PAA scaffold.
ContributorsLiu, Chongji (Author) / Massia, Stephen (Thesis advisor) / Pizziconi, Vincent (Committee member) / Pauken, Christine (Committee member) / Arizona State University (Publisher)
Created2014
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
Medical errors are now estimated to be the third leading cause of death in the United States (Makary & Daniel, 2016). Look-alike, sound- alike prescription drug mix-ups contribute to this figure. The US Food and Drug Administration (FDA) and Institute for Safe Medication Practices (ISMP) have recommended the use of Tall Man lettering since 2008, in which dissimilar portions of confusable drug names pairs are capitalized in order to make them more distinguishable. Research on the efficacy of Tall Man lettering in differentiating confusable drug name pairs has been inconclusive and it is imperative to investigate potential efficacy further considering the clinical implications (Lambert, Schroeder & Galanter, 2015). The present study aimed to add to the body of research on Tall Man lettering while also investigating another possibility for the mechanism behind Tall Man’s efficacy, if it in fact exists. Studies indicate that the first letter in a word offers an advantage over other positions, resulting in more accurate and faster recognition (Adelman, Marquis & Sabatos-DeVito, 2010; Scaltritti & Balota, 2013). The present study used a 2x3 repeated measures design to analyze the effect of position on Tall Man lettering efficacy. Participants were shown a prime drug, followed by a brief mask, and then either the same drug name or its confusable pair and asked to identify whether they were the same or different. All participants completed both lowercase and Tall Man conditions. Overall performance measured by accuracy and reaction time revealed lowercase to be more effective than Tall Man. With regard to the position of Tall Man letters, a first position advantage was seen both in accuracy and reaction time. A first position advantage was seen in the lowercase condition as well, suggesting the location of the differing portion of the word matters more than the format used. These findings add to the body of inconclusive research on the efficacy of Tall Man lettering in drug name confusion. Considering its impact on patient safety, more research should be conducted to definitively answer the question as to whether or not Tall Man should be used in practice.
ContributorsKnobloch, Ashley (Author) / Branaghan, Russell (Thesis advisor) / Cooke, Nancy J. (Committee member) / Gray, Robert (Committee member) / Arizona State University (Publisher)
Created2017
Description
Previous literature was reviewed in an effort to further investigate the link between notification levels of a cell phone and their effects on driver distraction. Mind-wandering has been suggested as an explanation for distraction and has been previously operationalized with oculomotor movement. Mind-wandering’s definition is debated, but in this research it was defined as off task thoughts that occur due to the task not requiring full cognitive capacity. Drivers were asked to operate a driving simulator and follow audio turn by turn directions while experiencing each of three cell phone notification levels: Control (no texts), Airplane (texts with no notifications), and Ringer (audio notifications). Measures of Brake Reaction Time, Headway Variability, and Average Speed were used to operationalize driver distraction. Drivers experienced higher Brake Reaction Time and Headway Variability with a lower Average Speed in both experimental conditions when compared to the Control Condition. This is consistent with previous research in the field of implying a distracted state. Oculomotor movement was measured as the percent time the participant was looking at the road. There was no significant difference between the conditions in this measure. The results of this research indicate that not, while not interacting with a cell phone, no audio notification is required to induce a state of distraction. This phenomenon was unable to be linked to mind-wandering.
ContributorsRadina, Earl (Author) / Gray, Robert (Thesis advisor) / Chiou, Erin (Committee member) / Branaghan, Russell (Committee member) / Arizona State University (Publisher)
Created2019
Description
The medical field is constantly looking for technological solutions to reduce user-error and improve procedures. As a potential solution for healthcare environments, Augmented Reality (AR) has received increasing attention in the past few decades due to advances in computing capabilities, lower cost, and better displays (Sauer, Khamene, Bascle, Vogt, & Rubino, 2002). Augmented Reality, as defined in Ronald Azuma’s initial survey of AR, combines virtual and real-world environments in three dimensions and in real-time (Azuma, 1997). Because visualization displays used in AR are related to human physiologic and cognitive constraints, any new system must improve on previous methods and be consistently aligned with human abilities in mind (Drascic & Milgram, 1996; Kruijff, Swan, & Feiner, 2010; Ziv, Wolpe, Small, & Glick, 2006). Based on promising findings from aviation and driving (Liu & Wen, 2004; Sojourner & Antin, 1990; Ververs & Wickens, 1998), this study identifies whether the spatial proximity affordance provided by a head-mounted display or alternative heads up display might benefit to attentional performance in a simulated routine medical task. Additionally, the present study explores how tasks of varying relatedness may relate to attentional performance differences when these tasks are presented at different spatial distances.
Contributorsdel Rio, Richard A (Author) / Branaghan, Russell (Thesis advisor) / Gray, Rob (Committee member) / Chiou, Erin (Committee member) / Arizona State University (Publisher)
Created2017
Description
The American Diabetes Association reports that diabetes costs $322 billion annually and affects 29.1 million Americans. The high out-of-pocket cost of managing diabetes can lead to noncompliance causing serious and expensive complications. There is a large market potential for a more cost-effective alternative to the current market standard of screen-printed self-monitoring blood glucose (SMBG) strips. Additive manufacturing, specifically 3D printing, is a developing field that is growing in popularity and functionality. 3D printers are now being used in a variety of applications from consumer goods to medical devices. Healthcare delivery will change as the availability of 3D printers expands into patient homes, which will create alternative and more cost-effective methods of monitoring and managing diseases, such as diabetes. 3D printing technology could transform this expensive industry. A 3D printed sensor was designed to have similar dimensions and features to the SMBG strips to comply with current manufacturing standards. To make the sensor electrically active, various conductive filaments were tested and the conductive graphene filament was determined to be the best material for the sensor. Experiments were conducted to determine the optimal print settings for printing this filament onto a mylar substrate, the industry standard. The reagents used include a mixture of a ferricyanide redox mediator and flavin adenine dinucleotide dependent glucose dehydrogenase. With these materials, each sensor only costs $0.40 to print and use. Before testing the 3D printed sensor, a suitable design, voltage range, and redox probe concentration were determined. Experiments demonstrated that this novel 3D printed sensor can accurately correlate current output to glucose concentration. It was verified that the sensor can accurately detect glucose levels from 25 mg/dL to 400 mg/dL, with an R2 correlation value as high as 0.97, which was critical as it covered hypoglycemic to hyperglycemic levels. This demonstrated that a 3D-printed sensor was created that had characteristics that are suitable for clinical use. This will allow diabetics to print their own test strips at home at a much lower cost compared to SMBG strips, which will reduce noncompliance due to the high cost of testing. In the future, this technology could be applied to additional biomarkers to measure and monitor other diseases.
ContributorsAdams, Anngela (Author) / LaBelle, Jeffrey (Thesis advisor) / Pizziconi, Vincent (Committee member) / Abbas, James (Committee member) / Arizona State University (Publisher)
Created2017
Description
ABSTRACT
The cold and the flu are two of the most prevalent diseases in the world. Many over the counter (OTC) medications have been created to combat the symptoms of these illnesses. Some medications take a holistic approach by claiming to alleviate a wide range of symptoms, while others target a specific symptom. As these medications become more ubiquitous within the United State of America (USA), consumers form associations and mental models about the cold/flu field. The goal of Study 1 was to build a Pathfinder network based on the associations consumers make between cold/flu symptoms and medications. 100 participants, 18 years or older, fluent in English, and residing in the USA, completed a survey about the relatedness of cold/flu symptoms to OTC medications. They rated the relatedness on a scale of 1 (highly unrelated) to 7 (highly related) and those rankings were used to build a Pathfinder network that represented the average of those associations. Study 2 was conducted to validate the Pathfinder network. A different set of 90 participants with the same restrictions as those in Study 1 completed a matching associations test. They were prompted to match symptoms and medications they associated closely with each other. Results showered a significant negative correlation between the geodetic distance (the number of links between objects in the Pathfinder network) separating symptoms and medications and frequency of pairing symptoms with medication. This provides evidence of the validity of the Pathfinder network. It was also seen that, higher the relatedness rating between symptoms and medications in Study 1, higher the frequency of pairing symptom to medication in Study 2, and the more directly linked those symptoms and medications were in the Pathfinder network. This network can inform pharmaceutical companies about which symptoms they most closely associate with, who their competitors are, what symptoms they can dominate, and how to market their medications more effectively.
The cold and the flu are two of the most prevalent diseases in the world. Many over the counter (OTC) medications have been created to combat the symptoms of these illnesses. Some medications take a holistic approach by claiming to alleviate a wide range of symptoms, while others target a specific symptom. As these medications become more ubiquitous within the United State of America (USA), consumers form associations and mental models about the cold/flu field. The goal of Study 1 was to build a Pathfinder network based on the associations consumers make between cold/flu symptoms and medications. 100 participants, 18 years or older, fluent in English, and residing in the USA, completed a survey about the relatedness of cold/flu symptoms to OTC medications. They rated the relatedness on a scale of 1 (highly unrelated) to 7 (highly related) and those rankings were used to build a Pathfinder network that represented the average of those associations. Study 2 was conducted to validate the Pathfinder network. A different set of 90 participants with the same restrictions as those in Study 1 completed a matching associations test. They were prompted to match symptoms and medications they associated closely with each other. Results showered a significant negative correlation between the geodetic distance (the number of links between objects in the Pathfinder network) separating symptoms and medications and frequency of pairing symptoms with medication. This provides evidence of the validity of the Pathfinder network. It was also seen that, higher the relatedness rating between symptoms and medications in Study 1, higher the frequency of pairing symptom to medication in Study 2, and the more directly linked those symptoms and medications were in the Pathfinder network. This network can inform pharmaceutical companies about which symptoms they most closely associate with, who their competitors are, what symptoms they can dominate, and how to market their medications more effectively.
ContributorsTendolkar, Tanvi Gopal (Author) / Branaghan, Russell (Thesis advisor) / Chiou, Erin (Committee member) / Craig, Scotty (Committee member) / Arizona State University (Publisher)
Created2020
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 (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