Biomedical Engineering and Bioengineering Commons^™

3d Bioprinting Technology Innovation In Female Reproductive System, Siyao Chen, Tongxin Wang, Jiaqi Chen, Mingxing Sui, Luyao Wang, Xueyu Zhao, Jianqiao Sun, Yingli Lu

Department of Obstetrics & Gynecology Faculty Publications

Several diseases affect the female reproductive system, and both disease factors and treatments impact its integrity and function. Consequently, understanding the mechanisms of disease occurrence and exploring treatment methods are key research focuses in obstetrics and gynecology. However, constructing accurate disease models requires a microenvironment closely resembling the human body, and current animal models and 2D in vitro cell models fall short in this regard. Thus, innovative in vitro female reproductive system models are urgently needed. Additionally, female reproductive system diseases often cause tissue loss, yet effective tissue repair and regeneration have long been a bottleneck in the medical field. …

Coldstartcpi: Induced-Fit Theory-Guided Dti Predictive Model With Improved Generalization Performance, Qichang Zhao, Haochen Zhao, Linyuan Gao, Kai Zheng, Yajie Li, Qiao Ling, Jing Tang, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Predicting compound-protein interactions (CPIs) plays a crucial role in drug discovery. Traditional methods, based on the key-lock theory and rigid docking, often fail with novel compounds and proteins due to their inability to account for molecular flexibility and the high sparsity of CPI data. Here, we introduce ColdstartCPI, a framework inspired by induced-fit theory, which leverages unsupervised pre-training features and a Transformer module to learn both compound and protein characteristics. ColdstartCPI treats proteins and compounds as flexible molecules during inference, aligning with biological insights. It outperforms state-of-the-art sequence-based models, particularly for unseen compounds and proteins, and shows strong generalization capability …

Benchmarking Batch-Effect Correction Methods Towards The Construction Of A Triple-Negative Breast Cancer Cell Atlas, Peter Scheible, Amy H. Tang, Jing He, Jiangwen Sun

Computer Science Faculty Publications

Triple-negative breast cancer (TNBC) requires detailed cellular mapping given its aggressive nature, immense tumor heterogeneity and genetic diversity. We integrated 156,794 cells from six scRNA-seq datasets—including tumors, metastases, and cell lines—to build a TNBC scRNA cell atlas, focusing on batch effect mitigation while maintaining biological and molecular details. Preprocessing f ilters noise, normalizes data, and leverages PCA for integration readiness. We utilized scANVI, a semi-supervised tool, to align datasets, preserving TNBC’s complex tumor heterogeneity via marker annotations [1]. UMAPs demonstrate biological clustering in integrated data, contrasted with datasetdriven unintegrated patterns. Assessments verifying effective batch correction. This method aligns with NASA’s …

A Method For Ultrasound Servo Tracking For Puncture Needle, Shitong Ye, Bo Yang, Hao Quan, Shan Liu, Minyu Tang, Jiawei Tian

Electrical & Computer Engineering Faculty Publications

Computer-aided surgical navigation technology helps and guides doctors to complete the operation smoothly, which simulates the whole surgical environment with computer technology, and then visualizes the whole operation link in three dimensions. At present, common image-guided surgical techniques such as computed tomography (CT) and X-ray imaging (X-ray) will cause radiation damage to the human body during the imaging process. To address this, we propose a novel Extended Kalman filter-based model that tracks the puncture needle-point using an ultrasound probe. To address the limitations of Kalman filtering methods based on position and velocity, our method of Kalman filtering uses the position …

A Customized Large Single-Piece Bifrontal Implant For Post-Craniectomy Defect Reconstruction: A Case Study, Omid Ghaderzadeh, Ehsan Amirbeyk, Seyed Roholah Ghodsi, Zahra Namazi, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Background: Large bifrontal defects pose unique reconstruction challenges due to their complex curvature and mechanical requirements. This case demonstrated how computer-aided design/manufacturing (CAD/CAM) enabled precise single-piece polymethyl methacrylate (PMMA) implant fabrication, thereby overcoming traditional limitations. Case presentation: A 25-year-old male who had undergone bifrontal decompressive craniectomy suffered a severe traumatic brain injury. The autologous bone flap had been temporarily stored in a subcutaneous fat area of the abdomen for 3 months to preserve its viability. A secondary cranioplasty was then performed using titanium miniplates and self-tapping screws for final fixation. After 2 years, the patient developed empyema and a brain …

Identification Of Fiducial Points In Seismocardiographic Cycles Using Manual And Automated Annotation Methods, Jasmine-Vy T. Truong

Honors Undergraduate Theses

There is currently a need for complementary methods for non-invasive cardiac monitoring. Seismocardiography (SCG), the measurement of cardiac-induced vibrations at the chest surface, has shown potential clinical utility. Improving the reliability of detecting fiducial points of electrocardiography (ECG) and SCG, which collectively capture the electro-mechanical cardiac activities, could expand ECG/SCG utility as a low-cost, accessible tool for clinical assessment. This study identifies commonly accepted criteria for fiducial point detection in SCG and ECG through an extensive literature review and signal processing techniques. The previous criteria were evaluated to identify their strengths and weaknesses. Based on the findings, an improved set …

Automated Segmentation Of The Ulnar Nerve In Mri Using Deep Learning Techniques, Akhil Nagulapalli

Theses

Cubital Tunnel Syndrome (CuTS), a condition caused by compression of the ulnar nerve, results in numbness, tingling, pain, and even muscle atrophy, affecting fine motor skills and diminishing patient quality of life. Accurate diagnosis of CuTS is challenging, as current diagnostic methods—including clinical exams, nerve conduction studies, and unaided MRI—often lack the precision to reliably identify the nerve and detect compression in its early stages. Deep learning-based segmentation offers a promising solution, enabling precise and automated identification of nerve structures in MRI images, which could significantly improve diagnostic accuracy and support timely intervention.

A novel deep learning model for segmenting …

Physicochemical Property Effects On Immune Modulating Polymeric Nanoparticles: Potential Applications In Spinal Cord Injury, Daniel J. Kolpek, Jaechang Kim, Hisham Mohammed, John C. Gensel, Jonghyuck Park

Markey Cancer Center Faculty Publications

Nanoparticles (NPs) offer promising potential as therapeutic agents for inflammation-related diseases, owing to their capabilities in drug delivery and immune modulation. In preclinical studies focusing on spinal cord injury (SCI), polymeric NPs have demonstrated the ability to reprogram innate immune cells. This reprogramming results in redirecting immune cells away from the injury site, downregulating pro-inflammatory signaling, and promoting a regenerative environment post-injury. However, to fully understand the mechanisms driving these effects and maximize therapeutic efficacy, it is crucial to assess NP interactions with innate immune cells. This review examines how the physicochemical properties of polymeric NPs influence their modulation of …

Comparing Continuum And Direct Fiber Models Of Soft Tissues: An Ocular Biomechanics Example Reveals That Continuum Models May Artificially Disrupt The Strains At Both The Tissue And Fiber Levels, Xuehuan He, Mohammad R. Islam, Fengting Ji, Bingrui Wang, Ian A. Sigal

Mechanical Engineering Faculty Publications

Collagen fibers are the main load-bearing component of soft tissues but difficult to incorporate into models. Whilst simplified homogenization models suffice for some applications, a thorough mechanistic understanding requires accurate prediction of fiber behavior, including both detailed fiber-level strains and long-distance transmission. Our goal was to compare the performance of a continuum model of the optic nerve head (ONH) built using conventional techniques with a fiber model we recently introduced which explicitly incorporates the complex 3D organization and interaction of collagen fiber bundles [1]. To ensure a fair comparison, we constructed the continuum model with identical geometrical, structural, and boundary …

The Impact Of Cumulative And Acute Loading On Achilles Tendon Health, Performance, And Reported Pain In Collegiate Gymnasts, Julio Serrano Samayoa

Electronic Theses and Dissertations

Gymnasts are at a high risk of Achilles tendon (AT) injuries due to intense loads during takeoffs and landings. To better understand better the relationship between impact loading and its effects on tendon adaptation and athletic performance, this study uses Inertial Measurement Units (IMUs) to track AT loading across a collegiate gymnastics season. This data were compared against physiological and athletic performance metrics, obtained through force plates and ultrasound imaging, to explore how mechanical load influences reported pain and athletic performance. Results varied, with cumulative impacts being correlated with improved jump height (Spearman 0.362, Pearson 0.348), while peak power and …

Applications Of Computer Vision In Biomechanics And Orthopaedics, William Stewart Burton Ii

Electronic Theses and Dissertations

Machine learning has emerged as a key technology for enabling advanced computer vision systems. These systems now permeate many industries, and have enhanced traditional processes through autonomous interpretation of visual data. In the field of orthopaedics, the increasing prevalence of imaging highlights a need for similar tools. In many cases, however, direct translation of available frameworks fails to resolve the complex problems currently facing this field. Stringent performance requirements, complex visual environments, data scarcity, and implications for patient safety represent domain-specific factors which pose unique challenges to proven techniques. Novel approaches are needed to realize the full benefits of visual …

Use Of Electrical Bone Growth Stimulators In High-Risk Patients Following Spinal Fusion, Soumya Malhotra, Khavir Sharieff

HCA-NSU MD Research Day

Title: Use of Electrical Bone Growth Stimulators in High-Risk Patients Following Spinal Fusion Authors: Soumya Malhotra, BA., MS1 & Khavir Sharieff, DO, MBA2 1Class of 2027, Nova Southeastern University Dr. Kiran C. Patel College of Osteopathic Medicine, Fort Lauderdale, FL 2Assistant Professor of Surgery, Nova Southeastern University Dr. Kiran C. Patel College of Osteopathic Medicine, Tampa Bay, FLNova Southeastern University Dr. Kiran C. Patel College of Osteopathic Medicine Objective: This study aimed to elucidate the advantages of EBGSs following high-risk spinal fusions. Background: Pseudarthrosis is a condition where bones fail to fuse after an injury or surgery. It causes significant …

Editorial To Advances In Minimally Invasive Spine Surgery, Gabriel C. Tender, George A. Crabill

School of Medicine Faculty Publications

No abstract provided.

Assessing The Impact Of Femur Morphological Variations On Pediatric Hip Joint Biomechanics Using Statistical Shape Modeling, Tamara Chambers

Doctoral Dissertations and Master's Theses

This dissertation aimed to (1) quantify morphological variations in the pediatric hip joint and (2) evaluate the sensitivity of an infant musculoskeletal model (MSM) to these variations, considering hip joint center estimation errors. A shape statistical model (SSM) of decedent infant femurs from the Ortolani collection was created using ShapeWorks, capturing key morphological features, such as variations in the femoral neck-shaft and anteversion angles. Seven synthetic femurs were generated from the SSM to create SSM-informed MSMs, which were systematically evaluated through kinematics and kinetics analyses in OpenSim. Incorporating the SSM led to slight changes in the pediatric MSMs’ kinematics but …

Real-Time Navigation System For Breast Cancer Surgery With Pre- And Intra-Operative Imaging Using Neural Networks, Motaz Alqaoud

Biomedical Engineering Theses & Dissertations

Breast cancer is one of the most frequently diagnosed malignancies in women worldwide, necessitating precise diagnosis and treatment. Breast-conserving surgery (BCS) is the primary treatment for nonpalpable cases, yet current approaches often lack accuracy due to the absence of real-time 3D imaging during surgery. This limitation impairs surgeons’ ability to visualize tumor locations, compromising outcomes and potentially leading to repeat surgeries with higher risks, undesirable cosmetic results, increased costs, and, in some cases, mastectomy. Thus, there is a critical need for a navigation system to facilitate accurate tumor excision in nonpalpable breast cancer through real-time patient-specific 3D tracking.

This study …

Intercellular Mitochondrial Transfer Contributes To Microenvironmental Fate Redirection Of Mammary Cancer Cells, Julie Sofie Bjerring

Biomedical Sciences Theses & Dissertations

The dynamic cellular microenvironment, made up of resident cells and various macromolecules, differs markedly across tissues in the body. The multidirectional signals that cells receive from this microenvironment, along with the signaling they send back, heavily influence their physiology and behavior. Recent important findings have further validated this notion as the mammary microenvironment has been shown to suppress tumor progression by redirecting cancer cells to adopt a normal mammary epithelial progenitor fate in vivo. However, the mechanism(s) driving changes in metabolic reprogramming and cancer fate redirection is understudied. The work presented in this dissertation focuses on exploring the impact of …

Development Of A Haptic System For Robot-Assisted Femur Fracture Surgery, Fayez H. Alruwaili

Theses and Dissertations

Robot-assisted surgery has emerged within the field of surgical technology, driven by the need for greater accuracy and speed in the ongoing evolution of healthcare. This advancement has influenced numerous areas requiring enhancements to achieve optimal surgical results. However, surgical robotics tends to lack the surgeon’s connection to the operation, creating a gap in the intuitive skill set required for successful operations. The gap is seen through the lack of sense of touch, which may result in tissue damage and additional injury when the robot interacts with the patient. Furthermore, challenges faced during femur fracture surgery have positioned robot-assisted surgery …

Smart Cushion Device For Elderly Aging In Place, Anna Dion, Nate Colley, Leonardo Bravo

Biomedical Engineering

Our task at hand is to develop a consumer-focused solution for improving elder care to provide additional peace of mind for seniors and caregivers using technology to extend independent living. We intend to create a device that will improve the quality of life of elderly individuals living alone by encouraging periodical movement throughout the day, along with monitoring pressure distribution and alerting when pressure concentration is potentially harmful. It will also alert users to the presence of moisture which can arise from spills or incontinence. The key stakeholders of this project include elderly adults over the age of 65 who …

Toward Electrical Impedance Sensing Surgical Drill For Tissue Boundary Detection, Harshavardhan Devaraj

Dartmouth College Ph.D Dissertations

Dental implantation is an increasingly common procedure used to treat missing teeth. However, surgical drilling to place the implant poses a high risk of injury to critical anatomy, such as inferior alveolar nerve injury or maxillary sinus perforation. A real-time surgical feedback system sensing proximity of these critical anatomy could reduce injury risks. This dissertation investigates the development of such a system that incorporates an electrical impedance sensor into the tip of a surgical drill.

A simulation framework based on finite element method (FEM) was developed to optimize the sensor as it approached a high impedance boundary. The accuracy of …

Assisted Delivery Device, Rachel Rowe, Madeliene Mumford, Jenna Eissmann, Brittany Trinh

Biomedical Engineering

Current devices used to assist in complicated births present serious risks to both the mother and the fetus, which has caused a decline in the use of these devices over the last decade. This senior project team has proposed an alternative device that interfaces with the infant’s shoulders that would decrease these risks and contribute to the decrease of unnecessary c-sections due to device inadequacy. This Statement of Work includes research on the downfalls of current devices, existing patents, customer requirements, engineering specifications, and a design plan through December of this year. The next phase of this project will include …

Endoscopic Hyperspectral Imaging System To Discriminate Tissue Characteristics In Tissue Phantom And Orthotopic Mouse Pancreatic Tumor Model, Na Eun Mun, Thi Kim Chi Tran, Dong Hui Park, Jin Hee Im, Jae Il Park, Thanh Dat Le, Young Jin Moon, Seong-Young Kwon, Su Woong Yoo

Faculty, Staff and Student Publications

In this study, we developed an endoscopic hyperspectral imaging (eHSI) system and evaluated its performance in analyzing tissues within tissue phantoms and orthotopic mouse pancreatic tumor models. Our custom-built eHSI system incorporated a liquid crystal tunable filter. To assess its tissue discrimination capabilities, we acquired images of tissue phantoms, distinguishing between fat and muscle regions. The system underwent supervised training using labeled samples, and this classification model was then applied to other tissue phantom images for evaluation. In the tissue phantom experiment, the eHSI effectively differentiated muscle from fat and background tissues. The precision scores regarding fat tissue classification were …

Point-Of-Care Diagnostic Test For Beta-Thalassemia, Ran An, Umut A. Gurkan

Faculty Scholarship

Hemoglobin (Hb) disorders are among the most common monogenic diseases affecting nearly 7% of the world population. Among various Hb disorders, approximately 1.5% of the world population carries β-thalassemia (β-Thal), affecting 40,000 newborns every year. Early screening and a timely diagnosis are essential for β-thalassemia patients for the prevention and management of later clinical complications. However, in Africa, Southern Europe, the Middle East, and Southeast Asia, where β-thalassemia is most prevalent, the diagnosis and screening for β-thalassemia are still challenging due to the cost and logistical burden of laboratory diagnostic tests. Here, we present Gazelle, which is a paper-based microchip …

Nanoparticles For Applications In Specific Diagnostics And Precision Medicine, Naxhije Berisha

Dissertations, Theses, and Capstone Projects

Heterogeneity is common in the expression of cancer and treatment response. Precision medicine enables healthcare providers to tailor medical care to an individual's distinct genetic and environmental makeup. This customization has the potential to result in more efficient treatments while minimizing side effects. We believe that by studying the interface of nanotechnology and cancer medicine we can elucidate innovative solutions that address the challenges of disease heterogeneity. This includes advancements in drug delivery, formulations development, and diagnostic sensing. We highlight three studies that use nanotechnology for applications in precision medicine. In Chapter 2, we highlight design optimization of drug formulations …

Fibrin Glue Acutely Blocks Distal Muscle Contraction After Confirmed Polyethylene Glycol Nerve Fusion: An Animal Study., Alec H Fisher, Parker H Johnsen, Andrew Simon, Cameron J Burns, Vineeth Romiyo, Elliot B Bodofsky, Sebastian Vega, David A Fuller

Cooper Medical School of Rowan University Departmental Research

BACKGROUND: Polyethylene glycol (PEG) is a synthetic, biodegradable, and hyperosmotic material promising in the treatment of acute peripheral nerve injuries. Our team set out to investigate the impact of fibrin glue upon PEG fusion in a rat model.

METHODS: Eighteen rats underwent sciatic nerve transection and PEG fusion. Electrophysiologic testing was performed to measure nerve function and distal muscle twitch. Fibrin glue was applied and testing repeated. Due to preliminary findings, fibrin glue was applied to an uncut nerve in five rodents and testing was conducted before and after glue application. Mann-Whitney U tests were used to compare median values …

Mobilise-D Insights To Estimate Real-World Walking Speed In Multiple Conditions With A Wearable Device, Cameron Kirk, Arne Küderle, M Encarna Micó-Amigo, Tecla Bonci, Anisoara Paraschiv-Ionescu, Martin Ullrich, Abolfazl Soltani, Eran Gazit, Francesca Salis, Lisa Alcock, Kamiar Aminian, Clemens Becker, Stefano Bertuletti, Philip Brown, Ellen Buckley, Alma Cantu, Anne-Elie Carsin, Marco Caruso, Brian Caulfield, Andrea Cereatti, Lorenzo Chiari, Ilaria D'Ascanio, Judith Garcia-Aymerich, Clint Hansen, Jeffrey M Hausdorff, Hugo Hiden, Emily Hume, Alison Keogh, Felix Kluge, Sarah Koch, Walter Maetzler, Dimitrios Megaritis, Arne Mueller, Martijn Niessen, Luca Palmerini, Lars Schwickert, Kirsty Scott, Basil Sharrack, Henrik Sillén, David Singleton, Beatrix Vereijken, Ioannis Vogiatzis, Alison J Yarnall, Lynn Rochester, Claudia Mazzà, Bjoern M Eskofier, Silvia Del Din

Faculty, Staff and Student Publications

This study aimed to validate a wearable device's walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson's Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the …

Inflammatory Protein Elicitation In Response To Whole-Body Vibration Exposure, Nicholas Miller

Theses, Dissertations and Capstones

This study aimed to assess the effects of whole-body vibration (WBV) on the brain through changes in blood protein concentrations, seat and head accelerations, and symptomatology over time. Subjects were assigned to control, 1-hour, or 8-hour vibration exposure groups. Glial fibrillary acidic protein (GFAP) and S100B concentrations were measured. Root mean square average weighted vibration (A_ws), vibration dose value (VDV), and seat-to-head transmissibility (STHT) were calculated. There were no differences in GFAP (p = 0.79) or S100B (p = 0.97) concentrations between 1-hour and 8-hour subjects (p = 0.79). Average weighted head acceleration (p …

Novel Engineering Approaches For Orthopedic Injury Treatment And Infection Diagnosis, Cynthia Co

Bioengineering Dissertations - Archive

Bioengineering has made significant contributions to the treatment of orthopedic injury through interdisciplinary approaches. Central to these advancements are many orthopedic implants, including anchors and joint replacements, which have been designed to restore mobility. Despite their functional efficacy, these products have limited lifespan and are associated with many complications, such as implant-associated infection. The success of implant design and function, both in the short and long term, is paramount for enhancing patient outcomes and overall well-being. Therefore, my thesis work is dedicated to addressing these critical challenges, aiming to maximize their treatment effect while minimizing the implant-associated complications.

Long-term patient …

Guardians Of The Catheters, Interprofessional Collaboration Reduced Cauti Rates At Phfh, Dawn Doud, Angela Shemwell, Stephanie Brown, Tobi Bryan, Georgia Gauron, Tasha Anisimov, Peter Weitzman, Emma Peterson, Tiffanie Rampley

Articles, Abstracts, and Reports

Abstract Title: A Quality Improvement Project to Reduce CAUTIs on Inpatient Units

Objectives:

1. Participants will be able to understand how interprofessional collaboration contributed to CAUTI reduction on inpatient acute care units.
2. Participants will be able to understand education nurses completed to reduce CAUTI rates on inpatient acute care units.

Purpose/Aims:

To reduce CAUTI rates for adult inpatients admitted to the acute care units: Progressive Care Unit (PCU), Surgical/Orthopedics, Medical/Oncology, and the Intensive Care Unit (ICU).

Background

An increase in CAUTI rates for adults admitted to inpatient units was identified in January of 2024. The CAUTI rate at that time was …

Degradable Staples And Delivery Device, Meha Elango, Jessica Cabrera, Makayla Scarpitti, Kareemat Melaiye

Williams Honors College, Honors Research Projects

The scope of this project is to design a method to secure skin grafts to healthy tissue. The ultimate goal for the proposed method is to be dissolvable in some form. Currently, skin grafts procedures utilize staples in most cases to hold a skin graft in place, but there are disadvantages that come with it. Staples are easy to place, but time consuming during the removal procedure. They also cause a lot of pain and discomfort for the patient. The goal of this project is to determine a way a secure skin grafts to healthy skin in order to reduce …

Advancing Chronic Kidney Disease Prediction Through Machine Learning And Deep Learning With Feature Analysis, Shiddarth Dey Tusar, S. M. Ahad Ali Chowdhury, Md. Jalal Uddin Chowdhury, Rana M. Pir, H. M. Nur A. Alam, Muhammad Rezaur Rahman, Md. Nural Absar Siddiky, Muhammad Enayetur Rahman

Electrical & Computer Engineering Faculty Publications

Chronic Kidney Diesease (CKD) is a significant health issue, ranking as the fourth leading cause of mortality worldwide. The traditional diagnosis and treatment process, reliant on medical experts, is time-consuming. Therefore, thereis an urgent need for more efficient diagnostic methods to improve patient outcomes and reduce mortality rates. In this study, we employ Machine Learning (ML) and Deep Learning (DL) techniques to predict CKD based on important features. Feature analysis was performed using a correlation matrix and the LASSO algo-rithm to identify the most relevant features for model training. We evaluated several ML and DL classifiers, including Logistic Regression (LR), …