Computer Engineering Commons^™

Technocene, Vir Joseph Naidu

Masters Theses

Embodied human communication within the Anthropocene. Existing at the intersection of technology, and the body.

The design industry has developed technology that is, paradoxically, isolating. The exposure to a vast audience in the digital sphere has introduced new societal pressures, leading to a disconnection from our immediate surroundings, detached, and donning metaphorical masks. Technocene lives on the fringes of the discipline by blending conceptual thinking with practical application. Through curious, experimental artifacts, it prompts us to shed our masks and embrace vulnerability. Technocene endeavors to reimagine the human experience by acting as a discursive design project. It probes the boundaries …

Development And Feasibility Studies Of Ai-Powered Socially Assistive Robotics To Promote Wellbeing Of Persons With Alzheimer’S Disease And Related Dementias, Fengpei Yuan

Doctoral Dissertations

The number of persons living with Alzheimer's Disease and Related Dementias (PLWDs) has been keeping growing. In 2024, it is estimated that there will be approximately 6.7 million individuals living with Alzheimer's Dementia. This number will increase to about 14 million in 2060. Due to the damage in neurons, the capabilities of memory, thinking, and language will decline as the disease progress. As a result, persons with dementia will gradually withdraw from their social activities and become more dependent on others during their activities of daily living. Making it worse, our society is not ready for the increasing requirements of …

Towards A Wearable Device For Measuring Impedance Plethysmography Of The Radial Artery, Pritom Chowdhury

Dartmouth College Master’s Theses

Recent advancements in bioimpedance technology have demonstrated significant promise in the application of cardiac health monitoring. This research explores the design and development of a forearm-based wearable bioimpedance device for non-invasive measurement of heart rate and respiratory rate at an accuracy level comparable to medical-grade monitors. It utilizes a tetrapolar electrode configuration to analyze bioimpedance changes in the radial artery due to blood flow.

An ongoing aspect of this work involves the preliminary development of an embedded framework intended to integrate signal generation, acquisition, and processing within the device to achieve compact and efficient system design, anticipated to contribute to …

The Development And Testing Of A Gyroscope-Based Neck Strengthening Rehabilitation Device, Nicole D. Devos

Electronic Thesis and Dissertation Repository

Neck pain can be debilitating, and is experienced by the majority of people at some point over the course of their life. Resistance training has been shown to have significant improvement in pain or disability for patients. There are few options available for telerehabilitation, and the use of gyroscope stabilizers is proposed for this use. A biomechanics model of a head--neck--gyroscope system was created. In order to also model the dynamics of such a system, this work proposes a blended method using the Denavit--Hartenberg (DH) convention, popular in the field of robotics, with the Lagrangian mechanics approach to analyze an …

Steminism: Analyzing Factors That Improve Retention Of Women In Stem, Kira Carter, Jane Kelley, Jason Vasser-Elong, Rc Patterson

Dissertations

Our co-authored research ‘Steminism: Analyzing Factors That Improve Retention for Women as STEM Majors’ analyzed factors that contributed to the retention of women in science, technology, engineering, and mathematics (STEM) programs at Missouri University of Science & Technology (Missouri S&T). Women make up half of the US population, and while careers in (STEM) are an integral part of the US economy, women are underrepresented in these career fields. The purpose of our dissertation is to address the underrepresentation of women in STEM majors. Our methodology included homogeneous sampling to collect qualitative data. More specifically, we consulted with academic advisors and …

Mobile Robot Adhesion Methodology And Development Of An Automatous Robot Module, Lauren Baird, Zachariah Stone, Madison Lemons, Jonathon Moody

Williams Honors College, Honors Research Projects

Due to the increasing availability of space travel as not only a scientific exploration but a commercial exploration, there is a need for an onsite repair station that can be deployed in the event of aircraft maintenance, damage, or failure. We have been tasked with researching and creating a prototype of an automatous robot that can be attached to a spacecraft body, move along the surface while avoiding obstacles, scan for damage, 3D print a repair piece, and then make the repair, all without the need of direct human input. Our team, as will be discussed throughout, was tasked with …

Evaluating Eeg–Emg Fusion-Based Classification As A Method For Improving Control Of Wearable Robotic Devices For Upper-Limb Rehabilitation, Jacob G. Tryon

Electronic Thesis and Dissertation Repository

Musculoskeletal disorders are the biggest cause of disability worldwide, and wearable mechatronic rehabilitation devices have been proposed for treatment. However, before widespread adoption, improvements in user control and system adaptability are required. User intention should be detected intuitively, and user-induced changes in system dynamics should be unobtrusively identified and corrected. Developments often focus on model-dependent nonlinear control theory, which is challenging to implement for wearable devices.

One alternative is to incorporate bioelectrical signal-based machine learning into the system, allowing for simpler controller designs to be augmented by supplemental brain (electroencephalography/EEG) and muscle (electromyography/EMG) information. To extract user intention better, sensor …

Characterization And Estimation Of Musculoskeletal Pain Using Machine Learning, Boluwatife Faremi

Master's Theses

Traditional scales utilized for recording pain are known to be highly subjective and biased due to inaccuracies in recollecting actual pain intensities. As a result, machine learning (ML) models that are trained using these scores as ground truth are reported to have low performance for objective pain classification because of the huge disparity between what was felt in moments of pain and the scores recorded afterward.

In the present study, two devices were designed for gathering real-time, continuous in-session subjective pain scores and the recording of the autonomic nervous system (ANS) altered endodermal (EDA) activity. 24 participants were recruited to …

Dreamtemp: A Platform For Sleep Monitoring And Improvement, Michelle Lim, Kyle Pedersen, Will Cockrum

Interdisciplinary Design Senior Theses

With 70 million Americans suffering from chronic sleep disorders and only 7500 board-certified sleep physicians, a clear logistical problem exists that technological solutions may be able to address. The proliferation of IoT devices in homes and on our person presents a unique opportunity to improve sleep quality by leveraging the data they produce, and the control they provide to us over our everyday lives. DreamTemp is a platform for sleep monitoring and improvement that aims to improve an individual’s quality of sleep by dynamically adjusting the room temperature based on the user’s sleep cycle using a smart wearable and thermostat. …

Unveiling Pain: Wearables For Objective Pain Measurement, Hanqing Tang

Masters Theses

">">Pain perception is a subjective experience that differs significantly among individuals, often leading to inconsistencies in assessment and management. A critical issue within this context is the gender bias in pain evaluation, which contributes to unequal treatment and perpetuates gender inequality within the healthcare system. This thesis presents an in-depth investigation of the problem and proposes the development of a wearable device for objective pain assessment. Physiological parameters — Electrocardiography (ECG) can be collected from cardiac sound signals auscultated by fabrics via nanometre-scale vibrations. Machine learning methods can accurately classify heart rate and acute pain intensity of participants. …

Wearable Sensor Gait Analysis For Fall Detection Using Deep Learning Methods, Haben Girmay Yhdego

Electrical & Computer Engineering Theses & Dissertations

World Health Organization (WHO) data show that around 684,000 people die from falls yearly, making it the second-highest mortality rate after traffic accidents [1]. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. In light of the recent widespread adoption of wearable sensors, it has become increasingly critical that fall detection models are developed that can effectively process large and sequential sensor signal data. Several researchers have recently developed fall detection algorithms based on wearable sensor data. However, real-time fall detection remains challenging because of the wide …

Metabolomic Differentiation Of Tumor Core And Edge In Glioma., Mary E. Baxter

Electronic Theses and Dissertations

Glioma is one of the most aggressive forms of brain cancer. It has been shown that the microenvironments differ significantly between the core and edge regions of glioma tumors. This study obtained metabolomic profiles of glioma core and edge regions using paired glioma core and edge tissue samples from 27 human patients. Data was acquired by performing liquid-liquid metabolite extraction and 2DLC-MS/MS on the tissue samples. In addition, a boosted generalized linear machine learning model was employed to predict the metabolomic profiles associated with O-6-methylguanine-DNA methyltransferase (MGMT) promoter methylation.

A panel of 66 metabolites was found to be statistically significant …

Multi-View Contrastive Learning For Unsupervised Domain Adaptation In Brain-Computer Interfaces, Sepehr Asgarian

Electronic Thesis and Dissertation Repository

Electroencephalography (EEG) has been widely used to record electromagnetic fields for motor imagery (MI)-based brain-computer interfaces (BCIs). However, collecting MI signals is often time-consuming and challenging to classify due to the inter-subject variability of EEG signals. To address these issues, we propose a novel framework MACNet, which stands for Multi-view Adversarial Contrastive Network. MACNet employs a contrastive learning approach to learn spatial and temporal features in two views, using Riemannian and Euclidean encoders. By jointly extracting underlying features and learning domain-invariant representations in both source and target features, MACNet improves the alignment and accuracy. In addition, we propose a domain …

Experimental Evaluation Of Micro-Epidermal Actuators On Flexible Substrates, Courtney D. Bradley

Graduate Research Theses & Dissertations

Does embedding actuators in a flexible substrate increase their performance in hearing aids? What are the differences in damping experienced by actuators of different diameters and at different locations? At what frequency is peak acceleration achieved and what role does the size of the actuator and embedding it in a flexible substrate play? These questions will form the basis of this thesis. This work was done to develop a small non-invasive Band-Aid-©-like hearing aid. The novelty of this device requires a detailed analysis of piezoelectric actuators. This is a continuation of past students’ work on the topic. The main parameters …

Design And Fabrication Of A Force-Displacement Control Mechanism For Bone-Surgical Tool Testing, Kenneth Nwagu

Electronic Theses and Dissertations

This project focuses on the design and fabrication of an experimental setup for orthopedic-tool testing, tailored for a surgical instrumentation company. The multifaceted project encompasses a literature review, conceptual design, prototyping, and rigorous testing, resulting in a versatile control system capable of assessing various orthopedic tools, including bone drills, saws, burrs, and power handpieces.

Orthopedic surgical procedures (which include cutting and/or drilling into bone) often need to be performed on bones for faster recovery. The drilling and cutting process can cause an increase in temperature at the cutting site which can cause bone necrosis. The tools also need to be …

Machine Learning And Deep Learning Approaches For Gene Regulatory Network Inference In Plant Species, Sai Teja Mummadi

Dissertations, Master's Theses and Master's Reports

The construction of gene regulatory networks (GRNs) is vital for understanding the regulation of metabolic pathways, biological processes, and complex traits during plant growth and responses to environmental cues and stresses. The increasing availability of public databases has facilitated the development of numerous methods for inferring gene regulatory relationships between transcription factors and their targets. However, there is limited research on supervised learning techniques that utilize available regulatory relationships of plant species in public databases.

This study investigates the potential of machine learning (ML), deep learning (DL), and hybrid approaches for constructing GRNs in plant species, specifically Arabidopsis thaliana, …

Use Of Bioheat Modeling To Characterize And Optimize Implantable Medical Devices And Neuromodulation Technologies, Adantchede Louis Zannou

Dissertations and Theses

Medical device development includes prototyping, benchtop characterization, preclinical studies, and clinical trials. Understanding the limitations and potential adverse effects of medical devices prior to their administration in humans is a crucial first step. Optimizing medical devices is essential to employing technology and improving patients care. Computational modeling is widely adopted as a powerful tool to predict stimulation/recording parameter optimization, rapid electrode/device prototyping, investigating novel mechanism of action, and testing working principles of any medical devices. Many implantable neuromodulation technologies including Spinal Cord Stimulation (SCS), which provide substantial therapeutic benefit for patient population with lower back pain, produces heat via the …

Scalable Data-Driven Predictive Modeling And Analytics For Cho Process Development Optimization, Sarah Mbiki

All Dissertations

In 1982, the FDA approved the first recombinant therapeutic protein, and since then, the biopharmaceutical industry has continued to develop innovative and highly effective biological drugs for various illnesses¹. These drugs are produced using host organisms that are modified to hold the genetic encoding of the targeted protein¹. Of the many host organisms, Chinese hamster ovary (CHO) cells are often used due to capability to perform posttranslational modification (PTM): which allows human-like synthesis of proteins unlikely to invoke immunogenicity in humans ^1,2.

Despite all the positive attributes, many challenges are associated with CHO cell cultures, …

A Framework For Stable Robot-Environment Interaction Based On The Generalized Scattering Transformation, Kanstantsin Pachkouski

Electronic Thesis and Dissertation Repository

This thesis deals with development and experimental evaluation of control algorithms for stabilization of robot-environment interaction based on the conic systems formalism and scattering transformation techniques. A framework for stable robot-environment interaction is presented and evaluated on a real physical system. The proposed algorithm fundamentally generalizes the conventional passivity-based approaches to the coupled stability problem. In particular, it allows for stabilization of not necessarily passive robot-environment interaction. The framework is based on the recently developed non-planar conic systems formalism and generalized scattering-based stabilization methods. A comprehensive theoretical background on the scattering transformation techniques, planar and non-planar conic systems is presented. …

Material Characterization And Comparison Of Sol-Gel Deposited And Rf Magnetron Deposited Lead Zirconate Titanate Thin Films, Katherine Lynne Miles

Mechanical Engineering ETDs

Lead zirconate titanate (PZT) has been a material of interest for sensor, actuator, and transducer applications in microelectromechanical systems (MEMS). This is due to their favorable piezoelectric, pyroelectric and ferroelectric properties. While various methods are available to deposit PZT thin films, radio frequency (RF) magnetron sputtering was selected to provide high quality PZT films with the added capability of batch processing. These sputter deposited PZT films were characterized to determine their internal film stress, Young’s modulus, composition, and structure. After characterization, the sputtered PZT samples were poled using corona poling and direct poling methods. As a means of comparison, commercially …

Role Of Machine Learning In Early Diagnosis Of Kidney Diseases., Mohamed Nazih Mohamed Ibrahim Shehata

Electronic Theses and Dissertations

Machine learning (ML) and deep learning (DL) approaches have been used as indispensable tools in modern artificial intelligence-based computer-aided diagnostic (AIbased CAD) systems that can provide non-invasive, early, and accurate diagnosis of a given medical condition. These AI-based CAD systems have proven themselves to be reproducible and have the generalization ability to diagnose new unseen cases with several diseases and medical conditions in different organs (e.g., kidneys, prostate, brain, liver, lung, breast, and bladder). In this dissertation, we will focus on the role of such AI-based CAD systems in early diagnosis of two kidney diseases, namely: acute rejection (AR) post …

Application Of Deep Learning For Medical Sciences And Epidemiology Data Analysis And Diagnostic Modeling, Somenath Chakraborty

Dissertations

Machine Learning and Artificial Intelligence have made significant progress concurrent with new advancements in hardware and software technologies. Deep learning methods heavily utilize parallel computing and Graphical Processing Units(GPU). It is already used in many applications ranging from image classification, object detection, segmentation, cyber security problems and others. Deep Learning is emerging as a viable choice in dealing with today’s real-time medical problems. We need new methods and technologies in the field of Medical Science and Epidemiology for detecting and diagnosing emerging threats from new viruses such as COVID-19. The use of Artificial Intelligence in these domains is becoming more …

A Versatile Python Package For Simulating Dna Nanostructures With Oxdna, Kira Threlfall

Computer Science and Computer Engineering Undergraduate Honors Theses

The ability to synthesize custom DNA molecules has led to the feasibility of DNA nanotechnology. Synthesis is time-consuming and expensive, so simulations of proposed DNA designs are necessary. Open-source simulators, such as oxDNA, are available but often difficult to configure and interface with. Packages such as oxdna-tile-binding pro- vide an interface for oxDNA which allows for the ability to create scripts that automate the configuration process. This project works to improve the scripts in oxdna-tile-binding to improve integration with job scheduling systems commonly used in high-performance computing environments, improve ease-of-use and consistency within the scripts compos- ing oxdna-tile-binding, and move …

Radiomic Features To Predict Overall Survival Time For Patients With Glioblastoma Brain Tumors Based On Machine Learning And Deep Learning Methods, Lina Chato

UNLV Theses, Dissertations, Professional Papers, and Capstones

Machine Learning (ML) methods including Deep Learning (DL) Methods have been employed in the medical field to improve diagnosis process and patient’s prognosis outcomes. Glioblastoma multiforme is an extremely aggressive Glioma brain tumor that has a poor survival rate. Understanding the behavior of the Glioblastoma brain tumor is still uncertain and some factors are still unrecognized. In fact, the tumor behavior is important to decide a proper treatment plan and to improve a patient’s health. The aim of this dissertation is to develop a Computer-Aided-Diagnosis system (CADiag) based on ML/DL methods to automatically estimate the Overall Survival Time (OST) for …

Representation Learning For Chemical Activity Predictions, Mohamed S. Ayed

Dissertations, Theses, and Capstone Projects

Computational prediction of a phenotypic response upon the chemical perturbation on a biological system plays an important role in drug discovery and many other applications. Chemical fingerprints derived from chemical structures are a widely used feature to build machine learning models. However, the fingerprints ignore the biological context, thus, they suffer from several problems such as the activity cliff and curse of dimensionality. Fundamentally, the chemical modulation of biological activities is a multi-scale process. It is the genome-wide chemical-target interactions that modulate chemical phenotypic responses. Thus, the genome-scale chemical-target interaction profile will more directly correlate with in vitro and in …

Design Of Plastic Contaminant Eliminator In Seed Cotton, Joshua H. Tandio

Theses and Dissertations

Plastic contamination in cotton is a problem in cotton industry and researchers have worked on this problem with different approaches. This thesis documents the design of mechanical and electronic real-time systems for detecting and removing plastic contaminants. The mechanical system was designed to expose plastic embedded inside the seed cotton to the sensor and to separate plastic contaminated cotton from the process stream. The detection system consisted of an embedded computer interfaced with a USB camera and Neural Network (NN) software running in it. Two NN models were tested, a transfer learning model and a built-from-scratch original model. The original …

Generation, Analysis, And Evaluation Of Patient-Specific, Osteoligamentous, Spine Meshes, Austin R. Tapp

Biomedical Engineering Theses & Dissertations

Scoliosis, an abnormal curvature of the spine, is traditionally corrected with bracing treatments or by a highly invasive posterior spinal fusion (PSF) operation. These correction strategies are constrained by current imaging modalities, which fail to elucidate the soft tissue anatomy that is known to play a critical role in spinal stiffness and overall structure. Osteoligamentous segmentations of the spinal column offer a foundation for downstream finite element (FE) studies seeking to optimize bracing treatments or determine ideal surgical approaches.

This thesis presents methods for automatically and semi-automatically segmenting vertebrae and surrounding soft tissues of the spinal column using X-ray computed …

Interrelation Of Thermal Stimulation With Haptic Perception, Emotion, And Memory, Mehdi Hojatmadani

USF Tampa Graduate Theses and Dissertations

Haptics is an interdisciplinary field of science that deals with how humans perceive and respond to different sensory cues perceived through touch. Thermal haptics as a branch deals with how humans perceive the temperature sensation and respond to that. The process in which thermal perception occurs is well known to researchers. What seems missing in the literature is how temperature interacts or sometimes intervenes in other physiological and psychological aspects of our lives. In this research, a series of studies are presented where the main focus was how temperature and brain interact with each other to impede or enhance our …

Machine Learning Based Model For The Detection Of Brain Aneurysms From Mr Angiography, Katherine Becknell, Claire Bushnell, Rachel Fitzsimmons, Emily Sumner

Interdisciplinary Design Senior Theses

A brain aneurysm is a thin or weak spot on a blood vessel wall that expands and fills with blood. Brain aneurysms are very dangerous due to the fact that in most cases, patients do not show any symptoms. Because of this, aneurysms are difficult to diagnose unless it becomes very large or ruptures, resulting in fatal hemorrhage.

Aneurysms can be detected by a number of different brain imaging methods including Magnetic Resonance Imaging (MRI), Magnetic Resonance Angiography (MRA), Computed Tomography Angiography (CTA) and other imaging methods but for the sake of this report we will only be focusing on …

Development Of A Wearable Haptic Feedback Device For Upper Limb Prosthetics Through Sensory Substitution, Marco B.S. Gallone

Electronic Thesis and Dissertation Repository

Haptics can enable a direct communication pipeline between the artificial limb and the brain; adding haptic sensory feedback for prosthesis wearers is believed to improve operation without drawing too much of the user's attention. Through neuroplasticity, the brain can become more cognizant of the information delivered through the skin and may eventually interpret it as inherently as other natural senses. In this thesis, a wearable haptic feedback device (WHFD) is developed to communicate prosthesis sensory information. A 14-week, 6-stage, between subjects study was created to investigate the learning trajectory as participants were stimulated with haptic patterns conveying joint proprioception. 37 …