Biomedical Commons^™

Recent Progress In Microrna Detection Using Integrated Electric Fields And Optical Detection Methods, Logeeshan Velmanickam, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Low-cost, highly-sensitivity, and minimally invasive tests for the detection and monitoring of life-threatening diseases and disorders can reduce the worldwide disease burden. Despite a number of interdisciplinary research efforts, there are still challenges remaining to be addressed, so clinically significant amounts of relevant biomarkers in body fluids can be detected with low assay cost, high sensitivity, and speed at point-of-care settings. Although the conventional proteomic technologies have shown promise, their ability to detect all levels of disease progression from early to advanced stages is limited to a limited number of diseases. One potential avenue for early diagnosis is microRNA (miRNA). …

Integrating Therapy Into Play: Stand-On Ride-On For A Child With Cerebral Palsy, Kira Flanagan

UNF Graduate Theses and Dissertations

This study focuses on the development of an adaptive ride-on toy specifically designed for a 2.5-year-old child with spastic diplegic cerebral palsy. As a feasibility study, the primary objective of this innovative device is to enhance motor function, foster autonomy, and improve the overall quality of life for the child. The Power Mobility Device (PMD) integrates actuation and steering modifications, and a harness mechanism tailored to meet the child's unique needs. Comprehensive assessments of the child's spatiotemporal gait characteristics were conducted before and after a three-month usage period. The results reveal significant improvements in the child's ability to control dynamic …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

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 …

An Investigation Of Match For Lossless Video Compression, Brittany Sullivan-Reicks

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

A new lossless video compression technique, Match, is investigated. Match uses the similarity between the frames of a video or the slices of medical images to find a prediction for the current pixel. A portion of the previous frame is searched to find a matching context, which is the pixels surrounding the current pixel, within some distance centered on the current location. The best distance to use for each dataset is found experimentally. The matching context refers to the neighborhood of w, nw, n, and ne, where the pixel in the previous frame with the closest matching context becomes the …

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 …

Controlled Radiation Capsule For Precision And Rapid Cancer Treatment, Hoseon Lee, Zsolt Kollar, Bailey R. White, Junia Nguyen, David Roque, Sowjanya Palagani

Symposium of Student Scholars

This research aims to transform cancer treatment through the optimization of brachytherapy, with a focus on reducing treatment duration, setup complexities, and financial burdens, all while emphasizing patient safety. Patients living at a distance from radiation clinics, particularly those undergoing extended Low Dose Radiation brachytherapy, often struggle with the formidable financial challenges associated with securing nearby accommodations. In response to these issues, the research introduces a radiation capsule designed to condense the conventional six-month treatment period to approximately just one week, thereby significantly reducing the duration of required accommodations. This capsule is especially relevant considering the construction cost of $40 …

Improving Cellphone-Based Bio-Imaging Technique For Fluorescence Detection, Erteza T. Efaz

LSU Master's Theses

The research presented in this thesis focuses on the design, development, and evaluation of a fluorescence detection system. The system is implemented primarily as an Android application, Auto Camera, which leverages smartphone cameras to capture and analyze fluorescent images. The application provides a user-friendly interface with some configurable features like exposure time, ISO speed, and storage limit; as well as defining detection thresholds and setting acquisition intervals. This study begins with the architectural framework of the Android application, which is written in Java using Android Studio. The API compatibility is set to version 33, and users are prompted to grant …

Hierarchical Based Classifcation Method Based On Fusion Ofgaussian Map Descriptors Foralzheimer Diagnosis Using T1‑Weighted Magnetic Resonance Imaging, Nourhan Zayed, Shereen E. Morsy, Inas A. Yassine

Mechanical Engineering

Alzheimer’s disease (AD) is considered one of the most spouting elderly diseases. In 2015, AD is reported the US’s sixth cause of death. Substantially, non-invasive imaging is widely employed to provide biomarkers supporting AD screening, diagnosis, and progression. In this study, Gaussian descriptors-based features are proposed to be efcient new biomarkers using Magnetic Resonance Imaging (MRI) T1-weighted images to diferentiate between Alzheimer’s disease (AD), Mild Cognitive Impairment (MCI), and Normal controls (NC). Several Gaussian map-based features are extracted such as Gaussian shape operator, Gaussian curvature, and mean curvature. The aforementioned features are then introduced to the Support Vector Machine (SVM). …

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 …

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 …

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 …

Auto-Segmentation In Pancreatic And Liver Radiation Therapy, Cenji Yu

Dissertations and Theses (Open Access)

Background

Gastrointestinal cancers exhibit a high mortality rate compared to other cancer types. Among these, pancreatic cancer ranks as the fourth leading cause of cancer-related deaths worldwide. The five-year survival rate remains alarmingly low at a mere 9%. Hepatocellular carcinoma (HCC), another aggressive form of cancer, is rapidly becoming the primary cause of cancer-related deaths in the United States. The treatment of both liver cancer and pancreatic cancer heavily relies on a multidisciplinary approach. Innovative treatment strategies involving dose-escalated regimens, such as stereotactic body radiation therapy (SBRT), are emerging as an important pillar of the management of liver and pancreatic …

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 …

Accurate Orientation Control Of Tendon Driven Continuum Robots That Exhibit Elasticity, Manu Srivastava

All Dissertations

This dissertation makes new contributions to the modeling and implementation of Tendon Driven Continuum Robots (TDCRs). Specifically, motivated by 3D printing of concrete using a continuum hose robot in construction applications, we focus on TDCRs featuring compliance in the robot backbone and actuating tendons, e.g. surgical robots/endoscopes/catheters with tendon actuation. We expand previous mechanics-based models to show how and why such compliance significantly restricts performance when traditional kinematics-based planning and control techniques are applied.

The main contribution of this work is a new Elasticity Compensation(EC) model that explains why the ad hoc approach of preloading/pretensioning the tendons compensates for compliance …

Using Machine Learning To Assist Auditory Processing Evaluation, Hasitha Wimalarathna, Sangamanatha Veeranna, Minh Vu Duong, Chris Allan Prof, Sumit K. Agrawal, Prudence Allen, Jagath Samarabandu, Hanif M. Ladak

Electrical and Computer Engineering Publications

Introduction: Approximately 0.2–5% of school-age children complain of listening difficulties in the absence of hearing loss. These children are often referred to an audiologist for an auditory processing disorder (APD) assessment. Adequate experience and training is necessary to arrive at an accurate diagnosis due to the heterogeneity of the disorder.

Objectives: The main goal of the study was to determine if machine learning (ML) can be used to analyze data from the APD clinical test battery to accurately categorize children with suspected APD into clinical sub-groups, similar to expert labels.

Methods: The study retrospectively collected data from 134 children referred …

An Enhanced Adaptive Learning System Based On Microservice Architecture, Abdelsalam Helmy Ibrahim, Mohamed Eliemy, Aliaa Abdelhalim Youssif

Future Computing and Informatics Journal

This study aims to enhance Adaptive Learning Systems (ALS) in Petroleum Sector in Egypt by using the Microservice Architecture and measure the impact of enhancing ALS by participating ALS users through a statistical study and questionnaire directed to them if they accept to apply the Cloud Computing Service “Microservices” to enhance the ALS performance, quality and cost value or not. The study also aims to confirm that there is a statistically significant relationship between ALS and Cloud Computing Service “Microservices” and prove the impact of enhancing the ALS by using Microservices in the cloud in Adaptive Learning in the Egyptian …

Visual Question Answering: A Survey, Gehad Assem El-Naggar

Future Computing and Informatics Journal

Visual Question Answering (VQA) has been an emerging field in computer vision and natural language processing that aims to enable machines to understand the content of images and answer natural language questions about them. Recently, there has been increasing interest in integrating Semantic Web technologies into VQA systems to enhance their performance and scalability. In this context, knowledge graphs, which represent structured knowledge in the form of entities and their relationships, have shown great potential in providing rich semantic information for VQA. This paper provides an abstract overview of the state-of-the-art research on VQA using Semantic Web technologies, including knowledge …

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 …