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Concussions and traumatic brain injuries are mechanical events which can derive from no specific activity or event. However, these injuries occur often during athletic and sporting events but many athletes experiencing these symptoms go undiagnosed and continue playing without proper medical attention. The current gold standard for diagnosing athletes with

Concussions and traumatic brain injuries are mechanical events which can derive from no specific activity or event. However, these injuries occur often during athletic and sporting events but many athletes experiencing these symptoms go undiagnosed and continue playing without proper medical attention. The current gold standard for diagnosing athletes with concussions is to have medical professionals on the sidelines of events to perform qualitative standardized assessments which may not be performed frequently enough and are not specialized for each athlete. The purpose of this report is to discuss a study sanctioned by Arizona State University's Project HoneyBee and additional affiliations to validate a third-party mouth guard device product to recognize and detect force impacts blown to an athlete's head during athletic activity. Current technology in health monitoring medical devices can allow users to apply this device as an additional safety mechanism for early concussion awareness and diagnosis. This report includes the materials and methods used for experimentation, the discussion of its results, and the complications which occurred and areas for improvement during the preliminary efforts of this project. Participants in the study were five non-varsity ASU Wrestling athletes who volunteered to wear a third-party mouth guard device during sparring contact at practice. Following a needed calibration period for the devices, results were recorded both through visual observation and with the mouth guard devices using an accelerometer and gyroscope. This study provided a sound understanding for the operation and functionality of the mouth guard devices. The mouth guard devices have the capability to provide fundamental avenues of research for future investigations.
ContributorsTielke, Austin Wyatt (Author) / Ross, Heather (Thesis director) / LaBelle, Jeffrey (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Atrial fibrillation, also known as Afib or AF, is the most common irregular heart rhythm among the United States adult population. Atrial fibrillation is characterized by an abnormal fibrillation of the upper chambers of the heart, known as the atria. When left chronically untreated, this condition may lead to insufficient

Atrial fibrillation, also known as Afib or AF, is the most common irregular heart rhythm among the United States adult population. Atrial fibrillation is characterized by an abnormal fibrillation of the upper chambers of the heart, known as the atria. When left chronically untreated, this condition may lead to insufficient systemic blood flow or the formation of blood clots. Atrial fibrillation has many modifiable risk factors, meaning contributing habits and practices within the patient's control that may worsen the condition. Communication of these modifiable risk factors to patients with atrial fibrillation is important in improving patient quality of life and for reduction of disease symptoms. The motivation for this study was to convey the potential of improved disease process by lifestyle modification to patients with atrial fibrillation.
ContributorsLehman, Jessica Lynn (Author) / Ross, Heather (Thesis director) / Kelly, Lesly (Committee member) / Arizona State University. College of Nursing & Healthcare Innovation (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
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Description

2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing

2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing fetal heart development but they warrant revalidation and adjustment. 377 normal fetuses with healthy mothers, 98 normal fetuses with diabetic mothers, and 37 fetuses with cardiomyopathy and diabetic mothers had their cardiac structural dimensions, cardiothoracic ratio, valve flow velocities, and heart rates measured by fetal ECHO in a retrospective chart review. Cardiac features were fitted to linear functions, with respect to gestational age, femur length, head circumference, and biparietal diameter and z-scores were created to model normal fetal growth for all parameters. These z-scores were used to assess what metrics had no difference in means between the normal fetuses of both healthy and diabetic mothers but differed from those diagnosed with cardiomyopathy. It was found that functional metrics like mitral and tricuspid E wave and pulmonary velocity could be important predictors for cardiomyopathy when fitted by gestational age, femur length, head circumference, and biparietal diameter. Additionally, aortic and tricuspid annulus diameters when fitted to estimated gestational age showed potential to be predictors for fetal cardiomyopathy. While the metrics overlapped over their full range, combining them together may have the potential for predicting cardiomyopathy in utero. Future directions of this study will explore creating a classifier model that can predict cardiomyopathy using the metrics assessed in this study.

ContributorsMishra, Shambhavi (Co-author) / Numani, Asfia (Co-author) / Sweazea, Karen (Thesis director) / Plasencia, Jonathan (Committee member) / Economics Program in CLAS (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
148229-Thumbnail Image.png
Description

2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing

2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing fetal heart development but they warrant revalidation and adjustment. 377 normal fetuses with healthy mothers, 98 normal fetuses with diabetic mothers, and 37 fetuses with cardiomyopathy and diabetic mothers had their cardiac structural dimensions, cardiothoracic ratio, valve flow velocities, and heart rates measured by fetal ECHO in a retrospective chart review. Cardiac features were fitted to linear functions, with respect to gestational age, femur length, head circumference, and biparietal diameter and z-scores were created to model normal fetal growth for all parameters. These z-scores were used to assess what metrics had no difference in means between the normal fetuses of both healthy and diabetic mothers, but differed from those diagnosed with cardiomyopathy. It was found that functional metrics like mitral and tricuspid E wave and pulmonary velocity could be important predictors for cardiomyopathy when fitted by gestational age, femur length, head circumference, and biparietal diameter. Additionally, aortic and tricuspid annulus diameters when fitted to estimated gestational age showed potential to be predictors for fetal cardiomyopathy. While the metrics overlapped over their full range, combining them together may have the potential for predicting cardiomyopathy in utero. Future directions of this study will explore creating a classifier model that can predict cardiomyopathy using the metrics assessed in this study.

ContributorsNumani, Asfia (Co-author) / Mishra, Shambhavi (Co-author) / Sweazea, Karen (Thesis director) / Plasencia, Jon (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05