Biomedical Engineering and Bioengineering Commons^™

Statistical Modeling Of Knee Morphology And Material Properties Considering Diverse Populations, Gabrielle Jeannine Kindy

Electronic Theses and Dissertations

Total Knee Arthroplasty (TKA) is a widely performed surgical procedure aimed at alleviating pain and restoring function in patients with severe knee osteoarthritis. Despite its general success, disparities in postoperative outcomes have been observed across different racial and ethnic groups, with minority populations often experiencing less favorable results. One potential avenue for improving the generalizability of orthopaedic implants is using Statistical Shape and Intensity Models (SSIMs), which can be used to incorporate patient variability directly into the orthopaedic medical device development workflow through population-based finite element analysis.

This work aimed to construct an SSIM from a diverse subject set, incorporating …

Single-Molecule Orientation Imaging Reveals The Nano-Architecture Of Amyloid Fibrils Undergoing Growth And Decay, Brian Sun, Tianben Ding, Weiyan Zhou, Tara S. Porter, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Amyloid-beta (Aβ42) aggregates are characteristic Alzheimer’s disease signatures, but probing how their nanoscale architectures influence their growth and decay remains challenging using current technologies. Here, we apply time-lapse single-molecule orientation-localization microscopy (SMOLM) to measure the orientations and rotational “wobble” of Nile blue (NB) molecules transiently binding to Aβ42 fibrils. We correlate fibril architectures measured by SMOLM with their growth and decay over the course of 5 to 20 min visualized by single-molecule localization microscopy (SMLM). We discover that stable Aβ42 fibrils tend to be well-ordered and signified by well-aligned NB orientations and small wobble. SMOLM also shows that increasing order …

Accessible Real-Time Eye-Gaze Tracking For Neurocognitive Health Assessments, A Multimodal Web-Based Approach, Daniel C. Tisdale

Master's Theses

We introduce a novel integration of real-time, predictive eye-gaze tracking models into a multimodal dialogue system tailored for remote health assessments. This system is designed to be highly accessible requiring only a conventional webcam for video input along with minimal cursor interaction and utilizes engaging gaze-based tasks that can be performed directly in a web browser. We have crafted dynamic subsystems that capture high-quality data efficiently and maintain quality through instances of user attrition and incomplete calls. Additionally, these subsystems are designed with the foresight to allow for future re-analysis using improved predictive models, as well as enable the creation …

Computational Microscopy For Biomedical Imaging With Deep Learning Assisted Image Analysis, Yuwei Liu

Dissertations

Microscopy plays a crucial role across various scientific fields by enabling structural and functional imaging with microscopic resolution. In biomedicine, microscopy contributes to basic research and clinical diagnosis. Conventionally, optical microscopy derives its contrast from the amplitude of the optical wave and provides visualization of the physical structure of the sample qualitatively. To understand the function at the cellular or tissue level, there is a need to characterize the sample quantitatively and explore contrast mechanisms other than light intensity. Image enhancement or reconstruction from microscopic imaging systems is known as computational microscopy, and it involves the application of computational techniques …

Comparing Proliferation Rates And Collagen Production Of Cells Treated With Cuhars, Katie Elizabeth Mckenzie

Master's Theses

Cartilage is the padding in joints that protects the bones and aids in motion. Problems with the cartilage in the knee can be caused by mechanical damage or diseases like osteoarthritis. Chondrocytes make cartilage. The objective of this study is to determine the doubling time of chondrocytes per passage. I also want to determine the base amount of collagen-II created by chondrocytes as they age. I also want to determine how long it takes CuHARS to break down in different cell medias. Chondrocytes, human dermal fibroblasts, and CRL 2303 cells were grown and cultured for over a year. During that …

Modeling Synergistic Effects Of Integrin And Tgf-Beta Signaling In Epithelial Mesenchymal Transition, Prerak Thakkar

Biology and Medicine Through Mathematics Conference

No abstract provided.

Evaluating Neuroimaging Modalities In The A/T/N Framework: Single And Combined Fdg-Pet And T1-Weighted Mri For Alzheimer’S Diagnosis, Peiwang Liu

McKelvey School of Engineering Graduate Student Theses & Dissertations

With the escalating prevalence of dementia, particularly Alzheimer's Disease (AD), the need for early and precise diagnostic techniques is rising. This study delves into the comparative efficacy of Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) and T1-weighted Magnetic Resonance Imaging (MRI) in diagnosing AD, where the integration of multimodal models is becoming a trend. Leveraging data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we employed linear Support Vector Machines (SVM) to assess the diagnostic potential of these modalities, both individually and in combination, within the AD continuum. Our analysis, under the A/T/N framework's 'N' category, reveals that FDG-PET consistently outperforms T1w-MRI across …

Sports Science: An Entrepreneurial Venture, Nicole J. Jones

Senior Honors Projects

In sports science, ensuring maximum athlete safety and optimizing data utilization are pivotal yet leave room for further work. My project, Unbeaten SafeWare, addresses these critical issues by focusing on two primary concerns: preventing heat-related and cardiac illnesses, which are significant causes of athlete fatalities, and enhancing the transparency and utility of sports data. This initiative involves developing a shirt integrated with sensors to monitor vital signs and an athlete management system to handle data input, storage, analysis, and accessibility for athletes.

The project has advanced through the efforts of a multidisciplinary team, which includes biomedical engineering undergraduates, two faculty …

Database And Machine Learning Model For Classifying Autism Spectrum Disorder From Smartphone Based Electroretinography, Rory Harris

Honors Scholar Theses

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that negatively affects a patient’s cognitive and communication aptitude and, therefore, can severely impact that patient’s quality of life. Because of this, early diagnosis is paramount. In recent studies, electroretinography (ERG), which is a measure of the retina’s electrical response to a brief flash of light into the eye, has shown promise in detecting ASD. Access to these scans can provide early diagnosis, improving well-being. Current ERG devices are very expensive due to their on board processing capabilities. This paper aims to create an ERG device using a smartphone as the main …

Identifying Temporomandibular Disorder Morphological Risk Factors Via Explainable Deep Learning And Multiscale Biomechanical Modeling, Shuchun Sun

All Dissertations

Clarifying multifactorial musculoskeletal disorder etiologies supports risk analysis and development of targeted prevention and treatment modalities. Deep learning enables comprehensive risk factor identification through systematic analysis of disease datasets but does not provide sufficient context for mechanistic understanding, limiting clinical applicability for etiological investigations. Conversely, multiscale biomechanical modeling can evaluate mechanistic etiology within the relevant biomechanical and physiological context. We propose a hybrid approach combining 3D explainable deep learning and multiscale biomechanical modeling; we applied this approach to investigate temporomandibular joint (TMJ) disorder etiology by systematically identifying risk factors and elucidating mechanistic relationships between risk factors and TMJ biomechanics and …

Mathematical Modeling For Dental Decay Prevention In Children And Adolescents, Mahdiyeh Soltaninejad

Dissertations

The high prevalence of dental caries among children and adolescents, especially those from lower socio-economic backgrounds, is a significant nationwide health concern. Early prevention, such as dental sealants and fluoride varnish (FV), is essential, but access to this care remains limited and disparate. In this research, a national dataset is utilized to assess sealants' reach and effectiveness in preventing tooth decay, particularly focusing on 2nd molars that emerge during early adolescence, a current gap in the knowledge base. FV is recommended to be delivered during medical well-child visits to children who are not seeing a dentist. Challenges and facilitators in …

Exploring Human Aging Proteins Based On Deep Autoencoders And K-Means Clustering, Sondos M. Hammad, Mohamed Talaat Saidahmed, Elsayed A. Sallam, Reda Elbasiony

Journal of Engineering Research

Aging significantly affects human health and the overall economy, yet understanding of the underlying molecular mechanisms remains limited. Among all human genes, almost three hundred and five have been linked to human aging. While certain subsets of these genes or specific aging-related genes have been extensively studied. There has been a lack of comprehensive examination encompassing the entire set of aging-related genes. Here, the main objective is to overcome understanding based on an innovative approach that combines the capabilities of deep learning. Particularly using One-Dimensional Deep AutoEncoder (1D-DAE). Followed by the K-means clustering technique as a means of unsupervised learning. …

La1-Xsrxcoo3 Perovskite Nanomaterial: Synthesis, Characterization, And Its Biomedical Application, Adhira Tippur, Anyet Shohag, Luke Franco, Ahmed Touhami, Swati Mohan, Mohammed Uddin

Research Symposium

Early cancer detection is paramount for effective treatment and potential cures. This research explores the application of perovskite materials, specifically Sr2+-doped Lanthanum Cobaltite (La1-xSrxCoO3) nanomaterials, in cancer detection, with a focus on rats as an experimental model. The ferroelectric nature of these materials, synthesized through a combination of sol-gel and molten-salt processes, was examined at varying Sr2+ doping levels (1-20 wt%). Rigorous characterization, employing X-ray diffraction and scanning electron microscopy, confirmed the uniform morphology of nano cubes, laying the foundation for subsequent investigations. The magnetic properties of the perovskite nanoparticles were probed, suggesting their potential as a diagnostic tool for …

Resolving The Nanoscale Structure Of Β-Sheet Peptide Self-Assemblies Using Single-Molecule Orientation–Localization Microscopy, Weiyan Zhou, Conor L. O'Neill, Tianben Ding, Oumeng Zhang, Jai S. Rudra, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Synthetic peptides that self-assemble into cross-β fibrils are versatile building blocks for engineered biomaterials due to their modularity and biocompatibility, but their structural and morphological similarities to amyloid species have been a long-standing concern for their translation. Further, their polymorphs are difficult to characterize using spectroscopic and imaging techniques that rely on ensemble averaging to achieve high resolution. Here, we utilize Nile red (NR), an amyloidophilic fluorogenic probe, and single-molecule orientation-localization microscopy (SMOLM) to characterize fibrils formed by the designed amphipathic enantiomers KFE8^L and KFE8^D and the pathological amyloid-beta peptide Aβ42. Importantly, NR SMOLM reveals the helical (bilayer) …

6d Single-Fluorogen Orientation-Localization Microscopy For Elucidating The Architecture Of Beta-Sheet Assemblies And Biomolecular Condensates, Tingting Wu, Weiyan Zhou, Jai S. Rudra, Rohit V. Pappu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

We develop six-dimensional single-molecule orientation-localization microscopy (SMOLM) to measure the 3D positions and 3D orientations simultaneously of single fluorophores. We show how careful optimization of phase and polarization modulation components can encode phase, polarization, and angular spectrum information from each fluorescence photon into a microscope’s dipole-spread function. We used the transient binding and blinking of Nile red (NR) to characterize the helical structure of fibrils formed by designed amphipathic peptides, KFE8^L and KFE8^D, and the pathological amyloid-beta peptide Aβ42. We also deployed merocyanine 540 to uncover the interfacial architectures of biomolecular condensates.

Mri Image Regression Cnn For Bone Marrow Lesion Volume Prediction, Kevin Yanagisawa

Theses and Dissertations

Bone marrow lesions (BMLs), occurs from fluid build up in the soft tissues inside your bone. This can be seen on magnetic resonance imaging (MRI) scans and is characterized by excess water signals in the bone marrow space. This disease is commonly caused by osteoarthritis (OA), a degenerative join disease where tissues within the joint breakdown over time [1]. These BMLs are an emerging target for OA, as they are commonly related to pain and worsening of the diseased area until surgical intervention is required [2]–[4]. In order to assess the BMLs, MRIs were utilized as input into a regression …

Rational Design Of Peptide-Based Materials Informed By Multiscale Molecular Dynamics Simulations, Dhwanit Rahul Dave

Dissertations, Theses, and Capstone Projects

The challenge of establishing a sustainable and circular economy for materials in medicine and technology necessitates bioinspired design. Nature's intricate machinery, forged through evolution, relies on a finite set of biomolecular building blocks with through-bond and through-space interactions. Repurposing these molecular building blocks requires a seamless integration of computational modeling, design, and experimental validation. The tools and concepts developed in this thesis pioneer new directions in peptide-materials design, grounded in fundamental principles of physical chemistry. We present a synergistic approach that integrates experimental designs and computational methods, specifically molecular dynamics simulations, to gain in-depth molecular insights crucial for advancing the …

Low Shear In Short-Term Impacts Endothelial Cell Traction And Alignment In Long-Term, Mohanish Chandurkar, Nikhil Mittal, Shaina P. Royer-Weeden, Steven D. Lehmann, Yeonwoo Rho, Sangyoon J. Han

Michigan Tech Publications

Within the vascular system, endothelial cells (ECs) are exposed to fluid shear stress (FSS), a mechanical force exerted by blood flow that is critical for regulating cellular tension and maintaining vascular homeostasis. The way ECs react to FSS varies significantly; while high, laminar FSS supports vasodilation and suppresses inflammation, low or disturbed FSS can lead to endothelial dysfunction and increase the risk of cardiovascular diseases. Yet, the adaptation of ECs to dynamically varying FSS remains poorly understood. This study focuses on the dynamic responses of ECs to brief periods of low FSS, examining its impact on endothelial traction-a measure of …

Low Shear In Short-Term Impacts Endothelial Cell Traction And Alignment In Long-Term, Mohanish K. Chandurkar, Nikhil Mittal, Shaina P. Royer-Weeden, Steven D. Lehmann, Yeonwoo Rho, Sangyoon J. Han

Michigan Tech Publications

Within the vascular system, endothelial cells (ECs) are exposed to fluid shear stress (FSS), a mechanical force exerted by blood flow that is critical for regulating cellular tension and maintaining vascular homeostasis. The way ECs react to FSS varies significantly; while high, laminar FSS supports vasodilation and suppresses inflammation, low or disturbed FSS can lead to endothelial dysfunction and increase the risk of cardiovascular diseases. Yet, the adaptation of ECs to dynamically varying FSS remains poorly understood. This study focuses on the dynamic responses of ECs to brief periods of low FSS, examining its impact on endothelial traction—a measure of …

Experimental Study Of Bent Glass Curtain Walls., Sarah Said Abd El Kariem, Moustafa El Shami, Mahmoud El Nagar

Journal of Engineering Research

A Bent Laminated Glass is commonly used in the residential and commercial structures, its methodology is not present in the curves and tables at the ASTM E1300. Therefore, it has become a need for architects to use basis for this type of glass. To the best of authors ‘knowledge, no one study the bent laminated glass in details. A variety of safety glass that has lately gained popularity in the construction sector is modern laminated glass. Given that it offers a safe failover capability, it is perfect for the automotive industry. Double-lite glass is produced using two or more …

A 3d Dlt View Correction Tool For Manual Digitizing: A Cross-Platform Application For Correcting Shifted Image Coordinates Prior To Object Coordinate Reconstruction, William Moynihan

Theses, Dissertations and Capstones

While 3D direct linear transformation is a versatile motion capture method, care must be taken so that the cameras are not bumped or adjusted between the object space calibration phase and the end of video recording. Disturbing the cameras during this time will misalign the view, making the movement data invalid for the associated calibration. The purpose of this study was to design and validate a cross-platform software application for transforming image coordinates from a bumped camera to be compatible with the object space calibration and to determine the relationship between reconstruction error and changes to bumped camera views.

For …

A Smart Energy-Efficient Hybrid Gait Monitoring System, Elsa Joy Harris

CGU Theses & Dissertations

Triboelectric nanogenerators are devices that harvest mechanical energy from the environment and turn it into electricity. By coupling the effect of contact electrification and electrostatic induction between two materials that come into contact and then separate they can convert the irregular, low frequency, waste biomechanical energy of human motion into useful electrical energy to run small body-worn electronics. This has shown promising results in multiple applications such as self-powered motion and haptic sensing, self-charging micro-storage devices, neuromorphic computing, and designing batteryless circuits to power small wearables. This work will investigate a smart energy-efficient hybrid gait monitoring system that is powered …

Human System Composite Performance Measures: General Systems Performance Theory Insights, Lawrence Disalvi

Bioengineering Dissertations - Archive

Composite Performance Measures (CPMs) of human performance are widely employed in applications that range from mundane to life-changing, yet they are frequently presented without explanation or reference to theoretical underpinnings. The conceptual soundness of a widely used CPM approach, based on additive combination of constituent components, has been called into question by Kondraske. He argues the relevance of General Systems Performance Theory (GSPT) and performance capacity envelope concepts when applied to multidimensional CPM measures.

To obtain evidence-based answers to assertions regarding CPM types and rationale employed in medical and non-medical contexts, a Systematic Descriptive Review was conducted. Separately, the GSPT-based …

Implementing Unmanned Aerial Vehicles To Collect Human Gait Data At Distance And Altitude For Identification And Re-Identification, Donn E. Bartram

Graduate Theses, Dissertations, and Problem Reports (ETD)

Gait patterns are a class of biometric information pertaining to the way a person moves and poses. Gait information is unique to each person and can be used to identify and reidentify people. Historically, this task has been achieved through the use of multiple ground-based imaging sensors. However, as Unmanned Aerial Vehicles (UAVs) advance, they present the opportunity to evolve the process of persons identification and re-identification. Collecting human gait data using UAVs at distances ranging from 20m to 500m and altitudes ranging from 0m to 120m is a challenging task. The current biometric data collection methods, primarily designed for …

Mivt: Medical-Informed Vision Transformer For Early Epilepsy Diagnosis, Md Masum Rana

Dissertations and Theses

Epilepsy is a neurological disorder characterized by recurrent, unprovoked seizures, and early diagnosis is crucial for effective management and treatment. However, the diagnosis of epilepsy, particularly in its early stages, remains challenging due to the subtle nature of seizures and the complexity of brain activity patterns. In this research, we introduce the Medical-Informed Vision Transformer (MIVT), a deep learning architecture specifically designed to improve early epilepsy diagnosis from multimodal neuroimaging data. Our model integrates insights from both medical knowledge and state-of-the-art Vision Transformers (ViTs) to enhance the accuracy and interpretability of seizure detection and localization. The MIVT leverages the rich …

Development Of A Modular Lab Automation System With Applications To Animal And Bacteria Cell Culture, Timothy William Hartman

Dissertations and Theses

The challenges faced while executing wet lab protocols encourage the development of automation systems to come alongside human scientists. Today’s cutting-edge experiments involve complex protocols with precise measurements usually performed manually. Even simpler biological protocols can be tedious and prone to error, as was seen during the COVID-19 pandemic and society’s demand for high-volume, rapid sample analysis. Moreover, reproducibility suffers when there is excessive variability and insufficient data. Here, we leveraged the Stanford Biodesign process to develop a modular lab automation system and image analysis workflow to address challenges like these. This flagship automation platform at The University of South …

Quantification Of Antiviral Drug Tenofovir (Tfv) By Surface-Enhanced Raman Spectroscopy (Sers) Using Cumulative Distribution Functions (Cdfs), Marguerite R. Butler, Jana Hrncirova, Meredith Clark, Sucharita Dutta, John B. Cooper

Chemistry & Biochemistry Faculty Publications

Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive spectroscopic technique that generates signal-enhanced fingerprint vibrational spectra of small molecules. However, without rigorous control of SERS substrate active sites, geometry, surface area, or surface functionality, SERS is notoriously irreproducible, complicating the consistent quantitative analysis of small molecules. While evaporatively prepared samples yield significant SERS enhancement resulting in lower detection limits, the distribution of these enhancements along the SERS surface is inherently stochastic. Acquiring spatially resolved SERS spectra of these dried surfaces, we have shown that this enhancement is governed by a power law as a function of analyte concentration. Consequently, by definition, …

Unlv Title Iii Aanapisi & Mcnair Scholars Institute Research Journal 2024, Jesica Godinez-Paredes, Kian Hassankhan, Apia Hickman, Robin Ruth Kee, Kevin Ayala Pineda, Briana Melendez, Kalli Ramos, Saturn L. Reyes, Fabian Leija, Selena Pepe, Silva Topchyan, Celeste Ainsley, Mayra Arzate, Jessica Balistreri, Zantana Ephrem, Mirella Jasso, Karl Panou, Nichole Pelaez, Miklo Alcala, Akshay Dave, Mey Mey Heng, Michael Finkle, Janessa Montenegro, Reynafe Naol Aniga, Victor Mejia, Angelica G. Diaz, Anayeli Flores-Garibay, Kari Lee Joe Goold, Samantha Hernandez, Lianelys Cabrera Martinez, Caitlin Reynolds, Kimberly N. Usbeck, Abdulrahman Alahdal, Angelica Diaz, Willaine Mae Kahano, Raquel Jackson, Cecia Ruiz-Hernandez, Kers Ung-Watson, Yessenia Henriquez, Vanessa Marie Booth, Alexia Brown, Darlyn Magana, Bianca Navarro, Nicholas Pereira, Gia Renemae Calip, Lucky Heng, Ralph Sagun, Lucas Abreu, Alexandra Maria Acosta, Tristan Benally, Cosset Hernandez Pena, Adrian Montenegro, Cierra Paaaina-Daquioag, Nicole Torosian, Tracy Fuentes, Julissa Martinez, Medina Mcallister, Michal Newhouse-Van Vlerin, Tiria Carr, Nima Abkenar, Isabella Aceituno, Yuhan Bi, Victoria Campos, Melika Cummings, Zachary J. Johnigan, Alexis Sotolongo-Marin

McNair Journal

Journal articles based on research conducted by undergraduate students in the AANAPISI, LSAMP, and McNair Scholars Program.

Table of Contents

About AANAPISI

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Dr. Keith Rogers, Vice President for Student Affairs

Ms. Zhanna Aronov, Associate Vice President for Retention & Outreach

Development Of A Two-Finger Haptic Robotic Hand With Novel Stiffness Detection And Impedance Control, Vahid Mohammadi, Ramin Shahbad, Mojtaba Hosseini, Mohammad Hossein Gholampour, Saeed Shiry Ghidary, Farshid Najafi, Ahad Behboodi

Mechanical & Aerospace Engineering Faculty Publications

Haptic hands and grippers, designed to enable skillful object manipulation, are pivotal for high-precision interaction with environments. These technologies are particularly vital in fields such as minimally invasive surgery, where they enhance surgical accuracy and tactile feedback: in the development of advanced prosthetic limbs, offering users improved functionality and a more natural sense of touch, and within industrial automation and manufacturing, they contribute to more efficient, safe, and flexible production processes. This paper presents the development of a two-finger robotic hand that employs simple yet precise strategies to manipulate objects without damaging or dropping them. Our innovative approach fused force-sensitive …

Detection Of Tooth Position By Yolov4 And Various Dental Problems Based On Cnn With Bitewing Radiograph, Kuo Chen Li, Yi-Cheng Mao, Mu-Feng Lin, Yi-Qian Li, Chiung-An Chen, Tsung-Yi Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Periodontitis is a high prevalence dental disease caused by bacterial infection of the bone that surrounds the tooth. Early detection and precision treatment can prevent more severe symptoms such as tooth loss. Traditionally, periodontal disease is identified and labeled manually by dental professionals. The task requires expertise and extensive experience, and it is highly repetitive and time-consuming. The aim of this study is to explore the application of AI in the field of dental medicine. With the inherent learning capabilities, AI exhibits remarkable proficiency in processing extensive datasets and effectively managing repetitive tasks. This is particularly advantageous in professions demanding …