Master of Science, The Ohio State University, 2017, Vision Science

Oyler School is located in one of the lowest socioeconomic areas in Cincinnati, Ohio. The OneSight Vision Center was established in 2012 to provide much needed eye care to children in Cincinnati. The purpose of this research study is to analyze the academic success of this group of inner-city students before and after receiving spectacle correction. In addition, the compliance rate of spectacle wear and a comparison of the IEP students to the non-IEP students from the Cincinnati school district are included. Eye examination records for 2,333 students were provided from 81 different schools in Cincinnati, which were all examined at the OneSight Vision Center during the 2012-2013 and 2013-2014 academic years. Analysis of the various eye examination components was conducted, and the data showed that many children from the clinic sample had myopia (37.2%), hyperopia (7.7%), and astigmatism (36.9%). In addition, many children exhibited phorias greater than 5pd (0.9%), strabismus (2.7%), convergence insufficiency (0.8%), and accommodative insufficiency (3.0%). All of the Oyler School students who received spectacles increased their average GPA by 0.14 points (p=0.17) two quarters after receiving spectacle correction. Myopes saw an increase in average GPA by 0.08 (p=0.50), hyperopes saw the greatest increase in GPA by 0.37 (p=0.34), and astigmats increased by 0.13 (p=0.45). Although none of these increases were statistically significant, a 0.37 increase in GPA two quarters after receiving vision correction is very meaningful. All groups of refractive error saw an increase in math and reading GPA scores, but not writing; however none of the changes were statistically significant. Large variability in GPA change and small sample sizes resulted in poor power (generally less than 20%) to detect statistically significant changes in our GPA scores. Only 28.9% of children who received glasses during the 2012-2013 school year wore their glasses to their 2013-2014 vison exa (open full item for complete abstract)

Master of Science (M.S.), University of Dayton, 2013, Electrical Engineering

We present a 3D reconstruction algorithm designed to support various automation and navigation applications. The algorithm presented focuses on the 3D reconstruction of a scene using only a single moving camera. Utilizing video frames captured at different points in time allows us to determine the depths of a scene. In this way, the system can be used to construct a point cloud model of its unknown surroundings. In this thesis, we present the step by step methodology of the development of a reconstruction technique. The original reconstruction process, resulting with a point cloud was computed based on feature matching and depth triangulation analysis. In an improved version of the algorithm, we utilized optical flow features to create an extremely dense representation model. Although dense, this model is hindered due to its low disparity resolution. As feature points were matched from frame to frame, the resolution of the input images and the discrete nature of disparities limited the depth computations within a scene. With the third algorithmic modification, we introduce the addition of the preprocessing step of nonlinear super resolution. With this addition, the accuracy of the point cloud which relies on precise disparity measurement has significantly increased. Using a pixel by pixel approach, the super resolution technique computes the phase congruency of each pixel's neighborhood and produces nonlinearly interpolated high resolution input frames. Thus, a feature point travels a more precise discrete disparity. Also, the quantity of points within the 3D point cloud model is significantly increased since the number of features is directly proportional to the resolution and high frequencies of the input image. Our final contribution of additional preprocessing steps is designed to filter noise points and mismatched features, giving birth to the complete Dense Point-cloud Representation (DPR) technique. We measure the success of DPR by evaluating the visual appea (open full item for complete abstract)

Doctor of Philosophy (PhD), Wright State University, 2015, Human Factors and Industrial/Organizational Psychology PhD

With the introduction of the next generation of aerial refueling tankers, such as the KC-46, boom operators will use relatively recently developed indirect view stereo displays in place of direct view crew stations. Existing vision standards for boom operators were developed during the 1950s and may not be adequate for medical screening for KC-46 boom operators. Mild anomalies in binocular alignment, currently allowed by USAF vision standards, may permit stereopsis, but may also predispose those individuals to visual complaints such as eye-strain or headaches when viewing stereoscopic displays. The purpose of this research was to measure individual differences in performance with the use of a simulated remote vision system (RVS) during a simulated aerial refueling task; and to evaluate the relationship between individual differences in refueling performance and individual measures of quality of vision. To accomplish this research, a simulated RVS aerial refueling crew station was developed based on specifications provided by the USAF KC-46 Program Office and The Boeing Company. Experiment 1 was designed to simulate a “fighter drag” operational scenario where a boom operator repeatedly refuels receiver aircraft. Twenty-seven participants with varying quality of vision were recruited for Experiment 1. Each participant's vision was tested using the existing USAF test battery and a battery of newly-developed computer-based vision tests. In Experiment 2, the same RVS simulation was used to evaluate the overall effect of stereo viewing condition on refueling performance (2D, normal stereo, and hyper-stereo). The results of Experiment 1 reveal that refueling performance and level of discomfort are clearly dependent on quality of vision. Although most participants were generally comfortable using the simulated RVS, a few participants reported high levels of discomfort. Two vision tests were highly correlated with aerial refueling performance: minimum contrast sen (open full item for complete abstract)

Master of Science (MS), Ohio University, 2004, Electrical Engineering & Computer Science (Engineering and Technology)

Implementation and evaluation of a general aviation synthetic vision display system.

Master of Science, The Ohio State University, 2013, Vision Science

The purpose of this experiment was to observe and classify the head and eye movements of experienced baseball players when they are trying to hit a baseball. More specifically, it was designed to determine if players track deep into the pitch trajectory when attempting to hit, and if they use a similar tracking strategy when taking a pitch. We hypothesized that the batsmen would utilize two separate tracking methods, one for taking and another for swinging. Subjects were tested using a pitching machine called the Flamethrower under two separate conditions, in one condition they were instructed to “track the ball like you are taking a pitch”, and in the second condition they were instructed to “swing at the pitches like you would in batting practice”. Tennis balls were pitched from a distance of 56.3 feet from the batter at a measured velocity of approximately 75 miles per hour. Eye movements were recorded with the ISCAN infrared eye tracker and horizontal head rotations were recorded with the 3DM-GX1 head tracker and the Flock of Birds head tracker. All head and eye recordings were temporally synchronized with each other and with ball position using software. Two subjects were enrolled in the study. Each subject viewed 50 pitches under the “take” condition and 40 pitches under the “swing” condition. A total of 180 pitches were successfully recorded and both subjects were able to track a tennis ball in both testing conditions. Thus, 180 pitches were analyzed. Mean gaze errors for both trials indicated that the subjects were able to accurately track the pitched tennis balls for a majority of the ball's flight path under each testing condition. Inter-subject comparison revealed the subjects exhibited similar tracking strategies in each condition, although one subject appeared to have less variability with his head and eye movements. Both subjects utilized different tracking strategies for taking versus swinging. In the “take” condition, the subjects u (open full item for complete abstract)

Master of Science, The Ohio State University, 2007, Graduate School

Doctor of Philosophy, Case Western Reserve University, 2024, Sociology

Despite the availability of many preventive measures, there are a vast number of people with vision loss. The World Health Organization (2022) estimated that there are 2.2 billion people who are visually impaired, with 43 million being blind. In the United States, 32.2 million adults have vision loss. It is estimated that 90% of vision loss could be prevented or treated. Sociological inquiry on vision impairment provides a deeper understanding of the vision loss experience by examining both micro and macro consequences of vision loss, such as economic strains, depression, decreased ability to perform daily activities, and decreased quality of life. Few studies analyze social barriers to accessing vision care. This research advances and expands research on vision impairment through analysis of the social barriers to preventive vision exams that can prevent or impede vision loss. It employs linear and logistic regression as well as descriptive statistics to provide a better understanding of the vision loss experience. It examines how social categories (age, gender, race, and ethnicity), human capital, and social and emotional support affect access to preventive eye exams. Second, it evaluates how general health and vision health affect access to preventive eye exams. Third, an evaluation of which factors affect general health and vision health. This work provides findings that can help opticians, optometrists, and ophthalmologists understand the needs of their patients and the unique barriers patients may have to access care. It can also be used by organizations and policymakers to recognize important current and future changes that are needed in organization structure.

Master of Science in Electrical Engineering, University of Dayton, 2024, Electrical Engineering

In this project, we developed new designs for event-based pixel sensors and their related biasing circuits for 130nm, 90nm, and 65nm silicon processes. This was done by selecting new width and length (W/L) ratios for each process, creating a new reset configuration, and modifying the designs of the bias current generators to work for smaller silicon processes. Through our simulations, we found that our design was able to generate the expected output behavior of an event camera to different photocurrent inputs. Additionally, we performed preliminary radiation analysis on the generated design for varying inputs and ion strikes. It was found that OFF event detections were more susceptible to false event triggers than ON events, as weaker ion strikes were able to trigger them.

Master of Science, The Ohio State University, 2024, Vision Science

Purpose: to investigate the utility and performance of a subjective and an objective meridional method of refraction on five additional keratoconic subjects and provide more critical evaluations of the conceptual approach, methods, and results from previous studies. Methods: Subjective and objective meridional refraction was performed on 25 subjects without cycloplegia. Four subjects had bilateral keratoconus and one had unilateral keratoconus. Targets for refraction were Gaussian-attenuated square wave gratings at four orientations (0⁰, 45⁰, 90⁰, 135⁰), with a bar width equal to 2x the subject's threshold letter size (i.e. for 20/20, 10 minarc/bar width, or 3 cycles/degree). The endpoint of the refraction was the spherical lens power required to achieve maximum grating contrast at each orientation. Lens power at each grating orientation was determined twice, and the spherocylindrical correction was derived from the dioptric power for those four orientations. Subjective refraction and visual acuity measurements were conducted using a manual minus-cylinder phoropter, while objective refraction relied on aberrometry measurement using a Wavefront Sciences COAS-CLAS 2D aberrometer. The objective refraction utilized Zernike coefficients obtained from aberrometry measurements to calculate spherocylindrical lens power that maximized contrast at eight orientations. Upon completion of both refractions, an adaptive staircase visual acuity measurement was conducted to assess the final refractive results, adjusting letter size based on subject responses to ensure an accurate threshold determination. The resulting data from each refraction in terms of final spherocylindrical power, visual acuity, and calculated retinal image were analyzed and compared. In addition to the meridional objective method, two other objective methods based on aberrometry (Visual Strehl Ratio and Minimized Root-Mean-Squared) were performed post-data collection on the data collected from all subjects (open full item for complete abstract)

Master of Science, The Ohio State University, 2024, Vision Science

The task of predicting the vertical location of an object when it arrives to an observer may be based on a combination of visual ball-flight cues and internal models of projectile motion, incorporating gravity, advance cues, and kinematic cues associated with a thrower's motion. The time required to efficiently process these visual cues to predict the ball's trajectory is unknown. The purpose of this experiment was to determine whether viewing an approaching ball for a longer period of time can improve estimates of the passing height of this ball when only visual cues from ball-flight are provided. A second goal was to determine whether heuristic information predominates over visual cues to object trajectory in estimating the passing height of approaching objects, and whether heuristic information is more likely to be used early in the ball's flight. Twenty subjects (12 males and 8 females, mean age 23.7±1.69) who had played baseball or softball at the high school level or above within the past 10 years participated. Subjects stood 40 feet from a pneumatic pitching machine that propelled tennis balls toward them at 3 speeds (76mph, 61mph, and 52mph). The subjects' vision was blocked with occluding spectacles at 100ms (duration 1) or 250ms (duration 2) after pitch release. Each combination of speed and viewing duration was randomly used 10 times. Subjects then indicated on a 2-meter ruler the height they expected the ball to arrive had they been able to view the entire duration of the ball's trajectory. The balls arrived at heights of about 99cm (fast speed), 59cm (medium speed), and 21cm (slow speed). The mean height responses at the fastest speed were 109cm (duration 1) and 100cm (duration 2). At the medium speed the mean responses were 98cm (duration 1) and 80cm (duration 2). At the slowest speed the mean responses were 88cm (duration 1) and 65cm (duration 2). Paired t-tests between the mean responses for the two viewing durations at each speed all showed s (open full item for complete abstract)

Master of Science, The Ohio State University, 2023, Vision Science

The purpose of this study was to survey sports vision practitioners to gather information on sports vision practice. The goal was to learn where opportunities are being found within sports vision and the details of practitioners' preferred practice patterns. Sixty-one sports vision practitioners answered questions on an online survey after providing informed consent. For those who answered the question regarding their profession, 87% were optometrists. The survey included multiple choice questions, along with a table of sports vision related tools. For the multiple choice questions, survey takers were asked questions about practitioner and athletic population demographics, sports vision assessment and training, and optical tints and nutraceuticals. Survey respondents indicated how often they employed each of the tools in the table. The number of responses for the multiple choice questions ranged from 42 to 61 and the number of responses per device in the matrix table range from 47 to 50. Devices in the matrix table were categorized three ways. Firstly, as analog and digital devices. Secondly, as devices that train the visual hardware versus visual software systems. Lastly, the devices were organized in a 4-tier system based on previously proposed hierarchical visual perceptual models. The survey results indicate that sports vision practitioners have found a wide range of opportunities to work with athletes across several sports and age groups as indicated by responses to questions about athletic patient population, characteristics of work with athletes, and about contracts with sports teams. The sports with athletes with whom the survey responders work (most commonly baseball, 71.15%) generally aligns with the published sports vision research, where baseball is the most studied population. There are discrepancies among the level of sport represented by the results of this survey (most commonly high schoolers, 75.4%) and the literature, where collegiate a (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2021, Electrical and Computer Engineering

The fields of computer vision and machine learning have made enormous strides in developing models which solve tasks only humans have been capable of solving. However, the models constructed to solve these tasks came at an enormous price in terms of computational resources and data collection. Motivated by the sustainability of continually developing models from scratch to tackle every additional task humans can solve, researchers are interested in efficiently constructing new models for developing solutions to new tasks. The sub-fields of machine learning devoted to this line of research go by many names. Such names include multi-task learning, transfer learning, and few-shot learning. All of these frameworks use the same assumption that knowledge should be shared across models to solve a set of tasks. We define knowledge as the set of conditions used to construct a model that solves a given task. By shared knowledge, we are referring to conditions that are consistently used to construct a set of models which solve a set of tasks. In this work, we address two sets of tasks posed in the fields of computer vision and machine learning. While solving each of these sets of tasks, we show how each of our methods exhibits a novel implementation of shared knowledge leading to many implications for future work in developing systems that further emulate the abilities of human beings. The first set of tasks fall within the sub-field of action analysis, specifically the recognition of intent. Instead of a data-driven approach, we construct a hand-crafted model to infer between intentional/non-intentional movement using common knowledge concepts known by humans. These knowledge concepts are ultimately used to construct an unsupervised method to infer between intentional and non-intentional movement across levels of abstraction. By layers of abstraction we mean that the model needed to solve the most abstract instances of intent recognition, is useful in developing models whi (open full item for complete abstract)

Master of Science, The Ohio State University, 2021, Electrical and Computer Engineering

Recent advances in machine learning, such as deep neural networks, have enabled applications like Autonomous Driving (AD), that are becoming increasingly popular. AD is one promising technology that has become the primary area of interest for the machine learning research communities as well as the industry in the current decade. It is clearly evident that self-driving vehicles could significantly aid in reducing road accidents and also make driving more efficient. Deep neural networks are used in solving challenging tasks in AD such as image and object recognition, motion planning, and behavior prediction. But the application of deep learning to self-driving turns out to be much more complicated than in other areas due to the high amount of uncertainty in the surrounding dynamic environment. Despite the complexities involved, there has been significant progress in this field and the self-driving pipeline is rapidly evolving. In this thesis, we address the problem of Semantic Segmentation and Traffic Sign Recognition (TSR) in an Autonomous Vehicle (AV). By addressing these issues, we tackle the problem of cybersecurity (in sensors) in AVs. Autonomous vehicles, as we know them, are cyber-physical systems that comprise various subsystems that communicate with one another to enable a vehicle to demonstrate autonomous behavior. The perception systems perceive the environment and pass data to the decision-making systems or compute units and these, in turn, feed the actuation decision to the actuation system. This amount of coupling between various sub-systems of an autonomous vehicle allows them to be vulnerable to malicious attacks from outside. Owing to the fact that most industries are headed towards fully autonomous vehicles in the near future, ensuring the safety and security of these vehicles is of utmost importance and hence paves way for a new area of research among the research communities as well as commercial companies. After discussing different approa (open full item for complete abstract)

Master of Science, The Ohio State University, 2021, Vision Science

Vision impairment is a public health problem currently affecting over 10 million people in the United States. Established vision health surveillance mechanisms individually fail to capture the complexities of vision impairment at a granular level. The purpose of this study is to develop a county-level needs assessment for primary vision care services by assessing the relationship between vision impairment prevalence, unmet vision care need prevalence, and the distribution of optometrists in Ohio using multiple publicly available databases. Data from the 2017 American Community Survey were used to determine county-level prevalence estimates for vision impairment. Data from the 2017 Ohio Medicaid Assessment Survey were used to estimate unmet vision care needs in each county. State licensure records were obtained from the Ohio Vision Professionals Board and used to determine the geographic distribution of optometrists. US Census Bureau data were used to determine county population estimates. Correlations between vision impairment prevalence and unmet vision care need prevalence were assessed using linear regression. Vision impairment and unmet need prevalence differences between visually impaired and non-visually impaired cohorts were stratified by age, sex, and Medicaid eligibility (<138% Federal Poverty Limit, FPL) and compared using ANOVA and paired t-test analyses. Correlations between vision impairment prevalence and unmet vision care need prevalence with available optometrists per 10,000 residents in each county were assessed using linear regression. County-level vision impairment prevalence ranged from 1.1% to 5.2% and unmet vision care need prevalence ranged from 6.2% to 15.5%. Vision impairment and unmet vision need were positively correlated (R2 = 0.32, p < 0.001). Adults at or below 138% FPL were significantly more likely to report unmet vision care needs than those above 138% FPL (p < 0.001). Women were more likely than men to be visually impaired (open full item for complete abstract)

Doctor of Philosophy (PhD), Wright State University, 2020, Computer Science and Engineering PhD

As the population of older individuals increases worldwide, the number of people with cardiovascular issues and diseases is also increasing. The rate at which individuals in the United States of America and worldwide that succumb to Cardiovascular Disease (CVD) is rising as well. Approximately 2,303 Americans die to some form of CVD per day according to the American Heart Association. Furthermore, the Center for Disease Control and Prevention states that 647,000 Americans die yearly due to some form of CVD, which equates to one person every 37 seconds. Finally, the World Health Organization reports that the number one cause of death globally is from CVD in the form of either myocardial infarctions or strokes. The primary ways of assisting individuals affected with CVD are from either improved treatments, monitoring research, or primary and secondary prevention measures. In the form of cardiovascular structural monitoring, there are multiple ways of viewing the human heart. That is, Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), Computed Tomography (CT), and Ultrasonography are the four fundamental imaging techniques. Though, continuous monitoring with these imaging techniques is far from currently possible. Large financial cost and size (MRI), radiation exposure (PET and CT), or necessary physician assistance (Ultrasonography) are the current primary problems. Though, of the four methodologies, Ultrasonography allows for multiple configurations, is the least expensive, and has no detrimental side effects to the patient. Therefore, in an effort to improve continuous monitoring capabilities for cardiovascular health, we design a novel wearable ultrasound vest to create a near 3D model of the heart in real-time. Specifically, we provide a structural modeling approach specific to this system's design via a Stereo Vision 3D modeling algorithm. Similarly, we introduce multiple Stochastic Petri Net (SPN) models of the heart for future functiona (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2017, Philosophy

One of the most defining features of Rene Descartes' philosophy is the nature and degree of his dualism. As conventional readings go, Descartes neatly divides reality into two radically distinct types of substances—mind and body—and never the two shall meet. I argue, however, that Descartes does not split the mind from body as cleanly as conventional readings might think, that the two metaphysical hemispheres are not entirely separate. There is a bridge linking the two together, and the road map for discovery is found in Descartes' theory of sensory perception. Descartes' views on sensory perception is the most apt topic in which to seek an understanding of the relationship between mind and body because, in general, it requires some explanation about how immaterial souls are informed by material bodies; that is, the topic demands that Descartes hypothesize about how perceptions—which he considers exclusive to minds—can be of things wholly distinct in kind, things that are essentially material. Throughout his writings, Descartes pays most attention to visual sensory perception, and so I follow in suit. Moreover, I concentrate on visual shape perception because, as I argue, understanding this aspect of Descartes' philosophy leads to insights about the precise relationship between mind and body. To give a feel for the overall shape of my reading, consider “veil of perception” interpretations of Descartes. Such readings understand Descartes as wedging a “third thing” between perceivers and the perceived object, standardly ascribing the “third thing” to the mind itself. On such readings of Descartes, sensory access to the physical world is mediated by mental images. So, according to these readings, one sees an idea of a tree, but not the tree itself. According to the reading of Descartes I offer, however, the veil is sheerer than previously thought. For I argue that the “third thing” bridging perceivers with the perceived belongs to bodily substance. In par (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 1979, Graduate School

Doctor of Philosophy, The Ohio State University, 1978, Graduate School

Doctor of Philosophy, The Ohio State University, 1971, Graduate School

Doctor of Philosophy, The Ohio State University, 1955, Graduate School