Biomedical Engineering and Bioengineering Commons^™

Computational Investigation Of The Interactions Between Bioactive Compounds And Biological Assemblies, Tye D. Martin

Biomedical Engineering ETDs

Small, biologically active molecules with unique properties and applications are potential solutions to a wide range of threats to global health including infectious agents and neurodegenerative disease. Experimental studies on a class of oligomeric p-phenylene ethynylenes (OPEs) have shown potential both as bioactive antimicrobials and fluorescent sensing agents for tracking amyloid-β (Aβ) aggregates found in Alzheimer’s Disease (AD). A second type of small molecule with potential applications in AD therapy, curcumin, has been found to interfere with Aβ fibril growth. Curcumin also attenuates Aβ-membrane interactions and Aβ toxicity. Our goal has been to use computational techniques to better understand the …

Statistical Learning Of Biomedical Non-Stationary Signals And Quality Of Life Modeling, Mahdi Goudarzi

USF Tampa Graduate Theses and Dissertations

Statistical learning is a set of tools for modeling and understanding complex datasets. It is a recently developed area in statistics and blends with parallel developments in computer science and, in particular, machine learning.

The classification of biomedical non-stationary signals such as Electroencephalogram (EEG) is always a challenging problem due to their complexity. The low spatial resolution on the scalp, curse of dimensionality, poor signal-to-noise ratio are disadvantages of working with biomedical signals. EEG signals are unstructured data which needs preprocessing steps to extract informative features which are measurable and predictive. In the first two chapters of this dissertation, EEG …

Improving 3d Printed Prosthetics With Sensors And Motors, Rachel Zarin

Honors Projects

A 3D printed hand and arm prosthetic was created from the idea of adding bionic elements while keeping the cost low. It was designed based on existing models, desired functions, and materials available. A tilt sensor keeps the hand level, two motors move the wrist in two different directions, a limit switch signals the fingers to open and close, and another motor helps open and close the fingers. All sensors and motors were built on a circuit board, programmed using an Arduino, and powered by a battery. Other supporting materials include metal brackets, screws, guitar strings, elastic bands, small clamps, …

Investigation Of Fundamental Principles Of Rigid Body Impact Mechanics, Khalid Alluhydan

Mechanical Engineering Research Theses and Dissertations

In impact mechanics, the collision between two or more bodies is a common, yet a very challenging problem. Producing analytical solutions that can predict the post-collision motion of the colliding bodies require consistent modeling of the dynamics of the colliding bodies. This dissertation presents a new method for solving the two and multibody impact problems that can be used to predict the post-collision motion of the colliding bodies. Also, we solve the rigid body collision problem of planar kinematic chains with multiple contacts with external surfaces.

In the first part of this dissertation, we study planar collisions of Balls and …

Using Feature Extraction From Deep Convolutional Neural Networks For Pathological Image Analysis And Its Visual Interpretability, Wei-Wen Hsu

Electrical & Computer Engineering Theses & Dissertations

This dissertation presents a computer-aided diagnosis (CAD) system using deep learning approaches for lesion detection and classification on whole-slide images (WSIs) with breast cancer. The deep features being distinguishing in classification from the convolutional neural networks (CNN) are demonstrated in this study to provide comprehensive interpretability for the proposed CAD system using the domain knowledge in pathology. In the experiment, a total of 186 slides of WSIs were collected and classified into three categories: Non-Carcinoma, Ductal Carcinoma in Situ (DCIS), and Invasive Ductal Carcinoma (IDC). Instead of conducting pixel-wise classification (segmentation) into three classes directly, a hierarchical framework with the …

Maximizing And Modeling Malonyl-Coa Production In Escherichia Coli, Tatiana Thompson Silveira Mello

LSU Master's Theses

In E. coli, fatty acid synthesis is catalyzed by the enzyme acetyl-CoA carboxylase (ACC), which converts acetyl-CoA into malonyl-CoA. Malonyl-CoA is a major building block for numerous of bioproducts. Multiple parameters regulate the homeostatic cellular concentration of malonyl-CoA, keeping it at a very low level. Understanding how these parameters affect the bacterial production of malonyl-CoA is fundamental to maximizing it and its bioproducts. To this end, competing pathways consuming malonyl-CoA can be eliminated, and optimal nutritional and environmental conditions can be provided to the fermentation broth. Most previous studies utilized genetic modifications, expensive consumables, and high-cost quantification methods, making …

Nano Fab Lab 63, Brian K. Deemer, Josh Clemons, Nick Brodine, Delaney Fitzsimmons

Mechanical Engineering

Lawrence Livermore National Laboratories (LLNL) has several steps in the production process for ceramic nanofiber tubes that they would like to improve - electrospinning, cutting, rolling, sealing and heat treating. We undertook the challenge to deliver LLNL with a semi-automated process that efficiently integrates the steps of cutting, rolling, and sealing to save time and improve control over end dimensions. In this document, we discuss the technical background of the manufacturing steps currently followed to create nanofiber tubes, identify which steps are incorporated in our prototype and explain how they will interface with one another, define the design requirements, present …

Predicting Tgf-Β-Induced Epithelial-Mesenchymal Transition Using Data Assimilation, Mario J. Mendez, Matthew J. Hoffman, Elizabeth M. Cherry, Dr. Christopher Lemmon, Seth Weinberg

Biology and Medicine Through Mathematics Conference

No abstract provided.

Age Dependent Regulation Of Cardiac Sodium Channel Gain Of Function, Madison Nowak, David Ryan King, Steven Poelzing, Seth Weinberg

Biology and Medicine Through Mathematics Conference

No abstract provided.

Coupled Influence Of Heart Rate Variability And Subcellular Calcium Heterogeneity On Cardiac Electromechanical Dynamics, Vrishti M. Phadumdeo, Seth H. Weinberg Ph.D

Biology and Medicine Through Mathematics Conference

No abstract provided.

Immunofluorescence Image Feature Analysis And Clustering Pipeline For Distinguishing Epithelial-Mesenchymal Transition, Shreyas Hirway, Nadiah Hassan, Dr. Christopher Lemmon, Dr. Seth Weinberg

Biology and Medicine Through Mathematics Conference

No abstract provided.

Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre

Honors Scholar Theses

Abnormal ocular motility is a common manifestation of many underlying pathologies particularly those that are neurological. Dynamics of saccades, when the eye rapidly changes its point of fixation, have been characterized for many neurological disorders including concussions, traumatic brain injuries (TBI), and Parkinson’s disease. However, widespread saccade analysis for diagnostic and research purposes requires the recognition of certain eye movement parameters. Key information such as velocity and duration must be determined from data based on a wide set of patients’ characteristics that may range in eye shapes and iris, hair and skin pigmentation [36]. Previous work on saccade analysis has …

Stability Analysis Of A More General Class Of Systems With Delay-Dependent Coefficients, Chi Jin, Keqin Gu, Islam Boussaada, Silviu-Iulian Niculescu

SIUE Faculty Research, Scholarship, and Creative Activity

This paper presents a systematic method to analyse the stability of systems with single delay in which the coefficient polynomials of the characteristic equation depend on the delay. Such systems often arise in, for example, life science and engineering systems. A method to analyze such systems was presented by Beretta and Kuang in a 2002 paper, but with some very restrictive assumptions. This work extends their results to the general case with the exception of some degenerate cases. It is found that a much richer behavior is possible when the restrictive assumptions are removed. The interval of interest for the …

Methods To Remotely Eliminate Biofilm From Medical Implants Using 2.4 Ghz Microwaves, Brett Glenn

Mechanical Engineering Undergraduate Honors Theses

Infections associated with biofilm growth are usually challenging to eradicate due to their high tolerance toward antibiotics [11, 12]. Biofilms often form on the inert surfaces of medically implanted devices [13]. No matter the sophistication, microbial infections can develop on all medical devices and tissue engineering constructs [12]. Related infections lead to 2 million cases annually in the U.S., costing the healthcare system over $5 billion in additional healthcare expenses [12].

Novel solutions to biofilm’s microbial colonization span the spectrum of engineering and science disciplines. Yet a practical solution still does not exist. The research presented here will explore a …

The Affective Perceptual Model: Enhancing Communication Quality For Persons With Pimd, Jadin Tredup

UNLV Theses, Dissertations, Professional Papers, and Capstones

Methods for prolonged compassionate care for persons with Profound Intellectual and Multiple Disabilities (PIMD) require a rotating cast of import people in the subjects life in order to facilitate interaction with the external environment. As subjects continue to age, dependency on these people increases with complexity of communications while the quality of communication decreases. It is theorized that a machine learning (ML) system could replicate the attuning process and replace these people to promote independence. This thesis extends this idea to develop a conceptual and formal model and system prototype.

The main contributions of this thesis are: (1) proposal of …

Feedforward And Feedback Signals In The Olfactory System, Srimoy Chakraborty

Graduate Theses and Dissertations

The conglomeration of myriad activities in neural systems often results in prominent oscillations. The primary goal of the research presented in this thesis was to study effects of sensory stimulus on the olfactory system of rats, focusing on the olfactory bulb (OB) and the anterior piriform cortex (aPC). Extracellular electrophysiological measurements revealed distinct frequency bands of oscillations in OB and aPC. However, how these oscillatory fluctuations help the animal to process sensory input is not clearly understood. Here we show high frequency oscillations in olfactory bulb carry feedforward signals to anterior piriform cortex whereas feedback from the aPC is predominantly …

Fluoride Removal From Water Using A 3d Printed Calcium Carbonate Filter, Sophia Bakar, David Kahler, Benjamin S. Goldschmidt

Undergraduate Research and Scholarship Symposium

Groundwater containing high concentrations of fluoride is the most common source of drinking water in rural areas in parts of east Africa, India, and China. The elevated levels of fluoride cause skeletal and dental fluorosis, which is the weakening and decay of bone structures due to the leeching of calcium from the body as calcium and fluoride bond by the process of adsorption. Over 150 million people are suffering from some form of fluorosis due to the consumption of groundwater. Calcium carbonate has been demonstrated to influence fluoride removal in several forms. To make fluoride removal a cost-effective and user-friendly …

Quantifying Iron Overload Using Mri, Active Contours, And Convolutional Neural Networks, Andrea Sajewski, Stacey Levine

Undergraduate Research and Scholarship Symposium

Iron overload, a complication of repeated blood transfusions, can cause tissue damage and organ failure. The body has no regulatory mechanism to excrete excess iron, so iron overload must be closely monitored to guide therapy and measure treatment response. The concentration of iron in the liver is a reliable marker for total body iron content and is now measured noninvasively with magnetic resonance imaging (MRI). MRI produces a diagnostic image by measuring the signals emitted from the body in the presence of a constant magnetic field and radiofrequency pulses. At each pixel, the signal decay constant, T2*, can be calculated, …

Primitive Palms: A Density Study On The Impacts Of Harvesting Natural Materials For Construction Purposes On Sumak Allpa Of The Amazon Rainforest, Zachary Bull

Independent Study Project (ISP) Collection

In an effort to better understand how rural construction techniques affect a surrounding environment, this study combines a density test of the natural building materials used in the construction of a school on Sumak Allpa island of the Orellana Province in the Amazon basin of Ecuador. The focus of the study measures the density of the bamboo species Guadua angustifolia and the Panama hat plant Carludovica palmata on the island while noting a comprehensive compilation of the techniques and materials used in the building process. Using a mix of plots and transects, a comparison of harvested material to remaining material …

Deswelling Induced Morphological Changes In Dual Ph And Temperature Responsive Ultra-Low Crosslinked Poly (N-Isopropyl Acrylamide)-Co-Acrylic Acid Microgels, Molla R. Islam, Maddie Tumbarello, L. Andrew Lyon

Engineering Faculty Articles and Research

Poly(N-isopropylacrylamide) microgels prepared without exogenous cross-linker are extremely “soft” as a result of their very low cross-linking density, with network connectivity arising only from the self-crosslinking of pNIPAm chains. As a result of this extreme softness, our group and others have taken interest in using these materials in a variety of bioengineering applications, while also pursuing studies of their fundamental properties. Here, we report deswelling triggered structural changes in poly(N-isopropylacrylamide-co-acrylic acid) (ULC10AAc) microgels prepared by precipitation polymerization. Dynamic light scattering suggests that the deswelling of these particles not only depends on the collapse of …

Estimating Variations In Metabolic Cost Within The Stride Cycle During Level And Uphill Walking, Arash Mohammadzadeh Gonabadi

UNO Student Research and Creative Activity Fair

Indirect calorimetry provides the average cost of a stride cycle and prevents from identifying which part of the gait cycle causes increased metabolic cost in patients, however, recent simulation methods allow estimating the time profile of metabolic cost within the stride cycle. In this study, we compare the estimations of the time profile of the metabolic cost of two simulation methods for level and uphill walking. We used kinematic, kinetic and electromyography data from level and uphill walking (one participant) to estimate the time profiles of metabolic cost using the muscle-level metabolic model of Umberger using electromyography and kinematic data …

Dynamic Light Scattering Optical Coherence Tomography To Probe Motion Of Subcellular Scatterers., Nico J J Arezza, Marjan Razani, Michael C Kolios

Medical Biophysics Publications

Optical coherence tomography (OCT) is used to provide anatomical information of biological systems but can also provide functional information by characterizing the motion of intracellular structures. Dynamic light scattering OCT was performed on intact, control MCF-7 breast cancer cells and cells either treated with paclitaxel to induce apoptosis or deprived of nutrients to induce oncosis. Autocorrelations (ACs) of the temporal fluctuations of OCT intensity signals demonstrate a significant decrease in decorrelation time after 24 h in both the paclitaxel-treated and nutrient-deprived cell groups but no significant differences between the two groups. The acquired ACs were then used as input for …

3d Microwave Tomography Using The Soft Prior Regularization Technique: Evaluation In Anatomically-Realistic Mri-Derived Numerical Breast Phantoms, Amir H. Golnabi, Paul M. Meaney, Shireen D. Geimer, Keith D. Paulsen

Department of Mathematics Faculty Scholarship and Creative Works

Objective: Fusion of magnetic resonance imaging (MRI) breast images with microwave tomography is accomplished through a soft prior technique, which incorporates spatial information (from MRI), i.e. accurate boundary location of different regions of interest, into the regularization process of the microwave image reconstruction algorithm. Methods: Numerical experiments were completed on a set of 3D breast geometries derived from MR breast data with different parenchymal densities, as well as a simulated tumor to evaluate performance over a range of breast shapes, sizes and property distributions. Results: When the soft prior regularization technique was applied, both permittivity and conductivity relative root mean …

Abso2luteu-Net: Tissue Oxygenation Calculation Using Photoacoustic Imaging And Convolutional Neural Networks, Kevin Hoffer-Hawlik, Geoffrey P. Luke

ENGS 88 Honors Thesis (AB Students)

Photoacoustic (PA) imaging uses incident light to generate ultrasound signals within tissues. Using PA imaging to accurately measure hemoglobin concentration and calculate oxygenation (sO₂) requires prior tissue knowledge and costly computational methods. However, this thesis shows that machine learning algorithms can accurately and quickly estimate sO₂. absO₂luteU-Net, a convolutional neural network, was trained on Monte Carlo simulated multispectral PA data and predicted sO₂ with higher accuracy compared to simple linear unmixing, suggesting machine learning can solve the fluence estimation problem. This project was funded by the Kaminsky Family Fund and the Neukom Institute.

Prediction Of The Outcome In Cardiac Arrest Patients Undergoing Hypothermia Using Eeg Wavelet Entropy, Hana Moshirvaziri

CGU Theses & Dissertations

Cardiac arrest (CA) is the leading cause of death in the United States. Induction of hypothermia has been found to improve the functional recovery of CA patients after resuscitation. However, there is no clear guideline for the clinicians yet to determine the prognosis of the CA when patients are treated with hypothermia. The present work aimed at the development of a prognostic marker for the CA patients undergoing hypothermia. A quantitative measure of the complexity of Electroencephalogram (EEG) signals, called wavelet sub-band entropy, was employed to predict the patients’ outcomes. We hypothesized that the EEG signals of the patients who …

Relaxed Mental State Detection Using The Emotiv Epoc And Adaptive Threshold Algorithms, Olin L. Anderson

EWU Masters Thesis Collection

The electroencephalogram (EEG) has proven to be useful in a wide variety of applications, including: diagnosis of mental disorders, psychological research, neurofeedback, and brain-computer interfacing. Most such applications of the EEG benefit from an ability to automatically detect when the subject is in a relaxed state. Recently, inexpensive and relatively easy to use EEG systems, with multiple electrodes, have become available at prices comparable to cellular phones or game machines. This project’s purpose is to investigate the feasibility of real-time classification of a subject's relaxation state using one such consumer-grade EEG system, the Emotiv Epoc. The subject's state is classified …

Gait And Postural Analysis In Healthy Young Adults And People With Parkinson's Disease, Aisha Joy Chen

CGU Theses & Dissertations

Postural analysis is the study of how the position of the body in any mode interacts with internal and external forces. This type of analysis is typically used to assess potential abnormalities in the balance control system and to understand how the balance control system changes with time. However, compared to other medical fields of study, postural analysis is relatively new [1]. In fact, although widely used in clinical and research studies, postural assessment methods are scientifically inaccurate, and some data collection methods are relatively expensive. A better understanding of the human balance control system could lead to more accurate …

Spatial Fingerprinting Of Biogenic And Anthropogenic Volatile Organic Compounds In An Arid Unsaturated Zone, Christopher T. Green, Wentai Luo, Christopher H. Conaway, Karl B. Haase, Ronald J. Baker

Chemistry Faculty Publications and Presentations

Subsurface volatile organic compounds (VOCs) can pose risks to human and environmental health and mediate biological processes. Volatile organic compounds have both anthropogenic and biogenic origins, but the relative importance of these sources has not been explored in subsurface environments. This study synthesized 17 yr of VOC data from the Amargosa Desert Research Site in Nevada with the goal of improving understanding of spatial and temporal variations that distinguish sources of VOCs from a landfill and from ambient sources including biogenic VOCs (bVOCs). Gas samples were collected from 1999 to 2016 from an array of shallow sample points (0.5- and …

A Survey Of Attention Deficit Hyperactivity Disorder Identification Using Psychophysiological Data, S. De Silva, S. Dayarathna, G. Ariyarathne, D. Meedeniya, Sampath Jayarathna

Computer Science Faculty Publications

Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurological disorders among children, that affects different areas in the brain that allows executing certain functionalities. This may lead to a variety of impairments such as difficulties in paying attention or focusing, controlling impulsive behaviours and overreacting. The continuous symptoms may have a severe impact in the long-term. This paper explores the ADHD identification studies using eye movement data and functional Magnetic Resonance Imaging (fMRI). This study discusses different machine learning techniques, existing models and analyses the existing literature. We have identified the current challenges and possible future directions …

End-To-End Learning Via A Convolutional Neural Network For Cancer Cell Line Classification, Darlington A. Akogo, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

Purpose: Computer vision for automated analysis of cells and tissues usually include extracting features from images before analyzing such features via various machine learning and machine vision algorithms. The purpose of this work is to explore and demonstrate the ability of a Convolutional Neural Network (CNN) to classify cells pictured via brightfield microscopy without the need of any feature extraction, using a minimum of images, improving work-flows that involve cancer cell identification.

Design/methodology/approach: The methodology involved a quantitative measure of the performance of a Convolutional Neural Network in distinguishing between two cancer lines. In their approach, they trained, validated and …