Engineering Commons^™

Shape Memory Alloy Capsule Micropump For Drug Delivery Applications, Youssef Mohamed Kotb

Theses and Dissertations

Implantable drug delivery devices have many benefits over traditional drug administration techniques and have attracted a lot of attention in recent years. By delivering the medication directly to the tissue, they enable the use of larger localized concentrations, enhancing the efficacy of the treatment. Passive-release drug delivery systems, one of the various ways to provide medication, are great inventions. However, they cannot dispense the medication on demand since they are nonprogrammable. Therefore, active actuators are more advantageous in delivery applications. Smart material actuators, however, have greatly increased in popularity for manufacturing wearable and implantable micropumps due to their high energy …

Affordable Bioprint Head-Adapter For 3d Printers, Andrew Ceralde, Dominic Drake, Noah Engles, Mohammad Alwan, Nevada Perry

Honors Capstones

Introduction: Addressing the need for affordable and accessible bioprinting technology, the Northern Illinois University bioprinting research and design project aims to democratize the field by developing an open source bioprint head. The initiative targets the prohibitive cost of commercial bioprinters by proposing an optimal design that can be integrated with widely available 3D printers, like the Creality Ender-3. This approach seeks to enable the widespread adoption of bioprinting technology, particularly for applications in tissue engineering and regenerative medicine.

Methods: Leveraging SolidWorks for design, the project employs a methodology that combines a precision extrusion system with thermal and UV crosslinking capabilities. …

The Contribution Of Micrornas To Rybp Silencing In Glioblastoma Multiforme, Alex B. Lee

Graduate Theses

Glioblastoma multiforme (GBM) is a highly aggressive and invasive tumor of the central nervous system (CNS). Survival rates are abysmal, with only 7.2% of patients alive 5-years after diagnosis. Because of this, understanding epigenetic alterations that give GBM tumors their aggressive phenotypes is critical for the development of more targeted and effective therapies. These alterations frequently affect a group of proteins called the Polycomb group proteins, which play important oncogenic and tumor suppressive roles in cancer. One Polycomb protein, the RING1- and YY1-binding protein (RYBP), is downregulated in a majority of GBM patients, suggesting a strong tumor suppressive property. In …

Low Impedance, Durable, Self-Adhesive Hydrogel Epidermal Electrodes For Electrophysiology Recording, Naiyan Wu

McKelvey School of Engineering Theses & Dissertations

Traditional electrodes used for electrophysiology recording, characterized by their hard, dry, and inanimate nature, are fundamentally mismatched with the soft, moist, and bioactive characteristics of biological tissues, leading to suboptimal skin-electrode interfaces. Hydrogel materials, mirroring the high water content and biocompatibility of biological tissues, emerge as promising candidates for epidermal electronic materials due to their adjustable physicochemical properties. However, challenges such as inadequate electrical conductivity, elevated skin impedance, unreliable adhesion in moist conditions, and performance decline from dehydration have significantly restricted the efficacy and applicability of hydrogel-based electrodes. In this thesis, we report a high-performance hydrogel epidermal electrode patch for …

Breast Cancer Risk In Women With Breast Bilateral Asymmetry: Machine Learning Based Risk Analysis And Mitigation Through Developing A Framework For Customized Bra Design, Xi Feng

Electronic Thesis and Dissertation Repository

Breast cancer is the most prevalent form of cancer globally, accounting for 12.5% of all new cases annually. Research has found a significant correlation between breast bilateral asymmetry and an increased risk of cancer, with women diagnosed with breast cancer having higher levels of bilateral asymmetrical breast volume. Unfortunately, 87% of women with breast asymmetry lack adequate tools for assessing their cancer risk. Early screening using bilateral asymmetry to predict a woman's long-term risk of breast cancer can help physicians make informed decisions about whether to recommend sequential imaging and the frequency of screening. Another important factor in understanding the …

Machine Learning Classifiers For Chronic Obstructive Pulmonary Disease Assessment Using Lung Ct Data., Halimah Alsurayhi

Electronic Thesis and Dissertation Repository

Chronic Obstructive Pulmonary Disease (COPD) is a condition characterized by persistent inflammation and airflow blockages in the lungs, contributing to a significant number of deaths globally each year. To guide tailored treatment strategies and mitigate future risks, the Global Initiative for Chronic Obstructive Lung Disease (GOLD) employs a multifaceted assessment system of COPD severity, considering patient's lung function, symptoms, and exacerbation history. COPD staging systems, such as the high-resolution eight-stage COPD system and the GOLD 2023 three staging systems, have been later developed based on these factors. Lung Computed Tomography (CT) is becoming increasingly crucial in investigating COPD as it …

Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso

Theses and Dissertations--Electrical and Computer Engineering

The emergence of deep learning models and their success in visual object recognition have fueled the medical imaging community's interest in integrating these algorithms to improve medical diagnosis. However, natural images, which have been the main focus of deep learning models and mammograms, exhibit fundamental differences. First, breast tissue abnormalities are often smaller than salient objects in natural images. Second, breast images have significantly higher resolutions but are generally heavily downsampled to fit these images to deep learning models. Models that handle high-resolution mammograms require many exams and complex architectures. Additionally, spatially resizing mammograms leads to losing discriminative details essential …

Non-Invasive Monitoring Device For Early Detection Of Breast Cancer Related Lymphedema, Amy Prendergast

Honors Theses and Capstones

Breast Cancer Related Lymphedema (BCRL) is a common co-morbidity in cancer survivors following neoadjuvant therapies such as chemotherapy, radiation, and/or surgery. It is brought about by the disruption in the lymphatic system (think lymph node biopsy) that leads to a buildup of lymphatic fluid in the arm. Current diagnostic strategies for this condition are merely retroactive, and fairly limited in the parameters that are examined to ensure patient well-being long term. We hypothesize that with an approach that mimics bioimpedance spectroscopy analysis, we will be able to provide a clinical support tool that would better determine early stages of lymphedema …

Design, Fabrication And Characterization Of Zero Power Sensor/Harvester For Smart Grid Applications, Zeynel Guler

Mechanical Engineering ETDs

This study presents a flexible sensor/harvester device to be used in both electromagnetic sensing and energy harvesting applications for smart grids. When a current passes through a wire, the sensor detects the magnetic field created by that current. The sensor magnet interacts with the wire magnetic field resulting in a transfer of energy through the piezoelectric cantilever. Piezoelectric, conductive, magnetic, and magnetostrictive composite thin films were prepared to fabricate this device.

Initially, the magnet of the cantilever was optimized considering its shape, thickness, length, taper angle etc. via both simulations and experiments. Peak to peak voltage versus cantilever position graph …

Development Of A 3d Printed Conductive Biopolymer For Cardiac Tissue Engineering, Britanny Lizeth Stark

Open Access Theses & Dissertations

Cardiovascular disease (CVD) is the leading cause of death in the US, with approximately 859,000 deaths each year. The major contributor to CVD is Acute Myocardial Infarction (AMI), which causes the death of approximately 25% of the cardiomyocytes present in the left ventricle of the heart. After AMI, the adult human heart has a very limited regenerative capacity. Moreover, the electrical propagation of the myocardium is severely disrupted, making the heart more susceptible to failure and patient death. However, current pharmacological treatments do not address the loss of cardiomyocytes and the disruption of electrical propagation in the heart. Tissue engineering …

Adaptive Personalized Drug Delivery Method For Warfarin And Anemia Management: Modeling And Control., Affan Affan

Electronic Theses and Dissertations

Personalized precision medicine aims to develop the appropriate treatments for suitable patients at the right time to obtain optimal results. Personalized medicine is challenging due to inter- and intra-patient variability, narrow therapeutic window, the effect of other medications, comorbidity (more than one disease at a time), nonlinear patient dynamics, and time-varying patient dose response characteristics which include bleeding (internal and external). This research aims to develop a framework for an adaptive personalized modeling and control method with minimum clinical patient specific dose response data for optimal drug dosing. The proposed methodology is applied to anemia and warfarin management. It is …

A Novel Method For Determining The Inherent Capabilities Of Computer And Robotic-Assisted Total Knee Arthroplasty Devices, Delaney R.G. Stevens

Electronic Thesis and Dissertation Repository

This thesis presents a method for evaluating and comparing assistive total knee arthroplasty (TKA) devices while controlling surgeon landmarking variability. To achieve consistent landmark selection by surgeons during TKA procedures, the method uses identical 3D-printed knees with indented landmarks. This method was used to compare a robotic and computer-assisted TKA device on three metrics: measurement accuracy, alignment accuracy, and cut-surface uniformity. Although both devices had considerable sagittal plane measurement errors, the robotic device had better measurement and alignment accuracy than the computer-assisted device. Furthermore, the robotic device's measuring error compensated for cutting errors, but the computer-assisted device's compounded them. However, …

Exploring The Use Of Audible Sound In Bone Density Diagnostic Devices, Evan J. Bess

Electronic Theses and Dissertations

Osteoporosis is a medical condition in which there is a progressive degradation of bone tissue that correlates with a characteristic decrease in bone density (BD). It is estimated that osteoporosis affects over 200 million people globally and is responsible for 8.9 million fractures annually. Populations at risk for developing osteoporosis include post-menopausal women, diabetic patients, and the elderly, representing a large population within the state of Maine. Current densitometric and sonometric devices used to monitor BD include quantitative computed tomography (QCT), dual-energy x-ray absorption (DXA), and ultrasound (QUS). All methods are expensive and, in the cases of QCT and DXA, …

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 …

Vertical Federated Learning Using Autoencoders With Applications In Electrocardiograms, Wesley William Chorney

Theses and Dissertations

Federated learning is a framework in machine learning that allows for training a model while maintaining data privacy. Moreover, it allows clients with their own data to collaborate in order to build a stronger, shared model. Federated learning is of particular interest to healthcare data, since it is of the utmost importance to respect patient privacy while still building useful diagnostic tools. However, healthcare data can be complicated — data format might differ across providers, leading to unexpected inputs and incompatibility between different providers. For example, electrocardiograms might differ in sampling rate or number of leads used, meaning that a …

An Automated, Deep Learning Approach To Systematically & Sequentially Derive Three-Dimensional Knee Kinematics Directly From Two-Dimensional Fluoroscopic Video, Viet Dung Nguyen

Doctoral Dissertations

Total knee arthroplasty (TKA), also known as total knee replacement, is a surgical procedure to replace damaged parts of the knee joint with artificial components. It aims to relieve pain and improve knee function. TKA can improve knee kinematics and reduce pain, but it may also cause altered joint mechanics and complications. Proper patient selection, implant design, and surgical technique are important for successful outcomes. Kinematics analysis plays a vital role in TKA by evaluating knee joint movement and mechanics. It helps assess surgery success, guides implant and technique selection, informs implant design improvements, detects problems early, and improves patient …

Towards Reliable Hepatocytic Anatomy Segmentation In Laparoscopic Cholecystectomy Using U-Net With Auto-Encoder, Koloud Najem Alkhamaiseh

Dissertations

Despite the advantages of minimally invasive surgeries that depend heavily on vision, the indirect access and lack of the 3D field of view of the area of interest introduce some complications in the desired procedures. Fortunately, the recorded videos from these procedures offer the opportunity for intra-operative and post-operative analyses, to improve future performance and safety.

Deep learning models for surgical video analysis could therefore support visual tasks such as identifying the critical view of safety (CVS) in laparoscopic cholecystectomy (LC), potentially contributing to the reduction of the current rates of bile duct injuries in LC. Most bile duct injuries …

Integration Of Biomedical Engineering And Computer Vision For Morphological Alteration Identification In Diabetic Cardiomyopathy: An Analysis And Evaluation Stra Tegy, Monica Delgado

Open Access Theses & Dissertations

Diabetic cardiomyopathy (DCM) is a type of heart disease that affects people with diabetes. It is characterized by changes in the structure and function of the heart, including thickening and stiffening of the heart muscle, impaired relaxation of the heart, and reduced pumping function. DCM is considered an ailment of the heart muscle and an increased risk factor in people with type 2 diabetes mellitus (T2DM). Although the exact mechanisms behind DCM are not fully understood, high blood glucose levels are known to contribute to the development and progression of the disease.While many options to manage and diagnose DCM have …

Augmented Human Inspired Phase Variable Using A Canonical Dynamical System, Timothy Driscoll

All Theses

Accurately parameterizing human gait is highly important in the continued development of assistive robotics, including but not limited to lower limb prostheses and exoskeletons. Previous studies introduce the idea of time-invariant real-time gait parameterization via human-inspired phase variables. The phase represents the location or percent of the gait cycle the user has progressed through. This thesis proposes an alternative approach for determining the gait phase leveraging previous methods and a canonical dynamical system.

Human subject experiments demonstrate the ability to accurately produce a phase variable corresponding to the human gait progression for various walking configurations. Configurations include changes in incline …

Novel Approach For Non-Invasive Prediction Of Body Shape And Habitus, Emma Young

Electronic Theses and Dissertations

While marker-based motion capture remains the gold standard in measuring human movement, accuracy is influenced by soft-tissue artifacts, particularly for subjects with high body mass index (BMI) where markers are not placed close to the underlying bone. Obesity influences joint loads and motion patterns, and BMI may not be sufficient to capture the distribution of a subject’s weight or to differentiate differences between subjects. Subjects in need of a joint replacement are more likely to have mobility issues or pain, which prevents exercise. Obesity also increases the likelihood of needing a total joint replacement. Accurate movement data for subjects with …

Piezoelectric And Conductive Polymer Based Flexible Devices Enabling Cardiovascular Health Sensing And Energy Harvesting, Andrew Closson

Dartmouth College Ph.D Dissertations

Piezoelectric materials show great promise for low-power wearable and implantable sensing, but their rigidity makes it challenging to integrate them with biological tissue. To address this, researchers have started exploring polymer-based functional materials that offer flexibility and are suitable for interfacing with the human body. However, these materials are still in their early stages, and a framework is necessary to illustrate how these materials, in conjunction with novel fabrication techniques and device designs, can enable the development of multi-functional sensing and energy harvesting devices.

This thesis utilizes highly scalable fabrication methods for functional polymers to build and test a flexible …

Approximate And Sample Entropy Of Center Of Pressure In Unperturbed Tandem Standing: Contribution Of Embedding Dimension And Tolerance, Jayla Mashae Wesley

Masters Theses

Approximate entropy (ApEn) and sample entropy (SampEn) are statistical methods designed to quantify the regularity or predictability of a time series. Although ApEn has been a prominent choice for use, it is currently unclear as to which method and parameter selection combination is optimal for its application in biomechanics. The goal of this thesis was to examine the difference between ApEn and SampEn related to center of pressure (COP) data during standing balance tasks, while also refining tolerance r, to determine entropy optimization. Six participants completed five 30-second, feet together and tandem standing, trials under eyes-open and eyes-closed conditions. Ground …

Computational Design Of Fiber-Optic Probes For Biosensing, Suwarna Karna

Electrical Engineering Theses

This thesis presents a study on the optical characteristics of hollow-core photonic crystal fibers (HC-PCFs) with a band gap cladding structure and their applications in optical fiber sensing. This 800B HC-PCF exhibited excellent optical properties and has a flexible structure, which makes them suitable for a wide range of industrial applications. Finite element simulations and structural optimization designs were conducted using the surface plasmon resonance (SPR) technique to determine the optimal performance parameters of the 800B HC-PCF. The fiber was further modified using the SPR technique to improve its practical detection capabilities. The performance of the modified fiber was observed …

Machine Learning For Biosensors, Gayathri Anapanani

Graduate Theses, Dissertations, and Problem Reports

Biosensors have become increasingly popular as diagnostic tools due to their ability to detect and quantify biological analytes in a wide range of applications. With the growing demand for faster and more reliable biosensing devices, machine learning has become a valuable tool in enhancing biosensor performance. In this report, we review recent progress in the application of machine learning to biosensors. We discuss the potential benefits of using machine learning in biosensors, including improved sensitivity, selectivity, and accuracy. We also discuss the various machine learning techniques that have been applied to biosensors, including data preprocessing, feature extraction, and classification and …

Design And Evaluation Of Fabric Cooling Channels For Twisted Coiled Actuators, Alex Lizotte

Electronic Thesis and Dissertation Repository

Twisted coiled actuators (TCAs) are biomimetic and inexpensive artificial muscles. To enable their integration into soft robotics, a novel cooling apparatus was designed, consisting of a fabric channel to house the TCA and a miniature air pump for forced convection. The channel was designed to be lightweight, flexible, and easy to integrate into a soft wearable robotic device. The effect that the channel dimensions had on TCA performance (cooling time, heating time, and stroke) was investigated by testing combinations of three widths (6, 8, and 10 mm) and three heights (4, 6, and 8 mm). In general, as the channel …

Diy Cell Incubator, Hayden James Jeanor

Electrical Engineering

The purpose of creating a cell Incubator is for the development of cell and tissue production in laboratory settings. Large scale research projects and the medical community grow cells for various reasons, including experiments and creating tissue for patients. However, they cannot simply depend on growing cells in a petri dish that sit on a rack at room temperature. To grow heathy cells in the fastest way possible, they use cell incubators. Cell incubators create an atmosphere within the incubation bay that is designed to promote cell growth. The three main components that need to be constantly regulated, using a …

Engineering 3d Bioprinted Cardiac Spheroidal Droplets With Cardiomyocytes And Cardiac Fibroblasts For Tissue Engineering And Drug Cytotoxicity Studies, Raven El Khoury

Open Access Theses & Dissertations

Engineering is the supreme human endeavor that involves harnessing the scientific understanding of the natural world to design and invent objects to improve the society around us. Biomedical engineering is the implementation of concepts acquired from engineering in biology and medicine that aims to improve human health through the integration of engineering with biomedical sciences. The mission of a biomedical engineer is to develop technologies that help advance the quality of peopleâ??s health using various tools and materials with one passion and goal: making the patient's life longer and easier. Tissue engineering is developed from the field of biomaterials and …

An Integrated Electronic-Skin Patch For Real-Time And Continuous Monitoring Of A Panel Of Biomarkers Combined With Drug Delivery, Tanzila Noushin

Electrical Engineering Theses

Inflammatory biomarkers present in the human body play a vital role in medical field by guiding the clinician in decision-making for many diseases. The levels of these inflammatory biomarkers are associated with the severity and progress of several diseases. Researchers have found that increasing severity of many diseases such as cardiovascular disease, after surgery infection, and adverse clinical outcomes due to infectious diseases, results in the elevation of the level of inflammatory biomarkers in human sweat. Furthermore, the inflammatory cytokines indicate the pathophysiology and prognosis of critically ill SARS‑CoV‑2 patients. In this thesis work, different sensors have been developed for …

Identifying And Minimizing Underspecification In Breast Cancer Subtyping, Jonathan Cheuk-Kiu Tang

Master's Theses

In the realm of biomedical technology, both accuracy and consistency are crucial to the development and deployment of these tools. While accuracy is easy to measure, consistency metrics are not so simple to measure, especially in the scope of biomedicine where prediction consistency can be difficult to achieve. Typically, biomedical datasets contain a significantly larger amount of features compared to the amount of samples, which goes against ordinary data mining practices. As a result, predictive models may fail to find valid pathways for prediction during training on such datasets. This concept is known as underspecification.

Underspecification has been more accepted …

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 …