Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons^™

Explorations Of Dna-Single-Walled Carbon Nanotube Interactions To Develop Multiplexed Molecularly Specific Biosensors For Inflammation, Amelia K. Ryan

Dissertations and Theses

Inflammatory cytokines such as interleukin-6 (IL-6) and interleukin-12 (IL-12) are central regulators of immune signaling and key biomarkers of disease, yet existing assays for their detection remain slow, invasive, and lack multiplexing ability. This dissertation advances the development of single-walled carbon nanotube (SWCNT) optical nanosensors capable of real-time, multiplexed, and molecularly specific cytokine detection through innovative use of single-stranded DNA (ssDNA) interfaces.

First, an IL-6-specific DNA aptamer was employed as both a dispersing agent and recognition probe for SWCNT fluorescence sensing. Sequence modifications, including anchor domains, truncations, and thermally induced refolding, were systematically tested to optimize sensitivity and selectivity. The …

Hypnosis And Mindfulness Audio Recordings For Reducing Fatigue In Individuals With Multiple Sclerosis: A Randomized Controlled Study, Mark P. Jensen, Susan Robles, Michael G. Nash, Susanne May, Dwan M. Ehde, Melissa A. Day, Owen Gottlieb, Laurence I. Sugarman, Kevin N. Alschuler

Articles

Background

Fatigue is a common problem in individuals with multiple sclerosis (MS).

Objective

The objective was to evaluate the effects on fatigue of having 4 weeks of

access to audio recordings of therapeutic hypnosis (HYP) and mindfulness meditation

(MM) practices.

Methods

A total of 333 individuals with MS and fatigue were randomly assigned to

one of the three treatment conditions for 28 weeks: (1) access to therapeutic HYP audio

recordings, (2) access to MM audio recordings, or (3) no access to recordings

(treatment as usual or TAU). Fatigue impact (primary outcome) and other outcomes

were assessed at 4, 16, and …

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 …

Advanced Nanocomposite-Based Electrochemical Sensor For Ultra-Sensitive Dopamine Detection In Physiological Fluids, Megha Shinde, Gymama Slaughter

Center for Bioelectronics Publications

This study presents a novel point-of-care electrochemical sensor for dopamine (DA) detection, featuring a flexible laser-induced graphene (LIG) modified with a unique nanocomposite comprising Nb₄C₃T_x MXene, polypyrrole (PPy), and iron nanoparticles (FeNPs). The LIG-Nb₄C₃T_x MXene-PPy-FeNPs is characterized by scanning electron microscopy to confirm the successful surface modification. The electrochemical performance of the fabricated sensor via cyclic voltammetry showed significant electrochemical activity upon Nb₄C₃T_x MXene-PPy-FeNPs nanocomposite modification of the LIG surface with an increased peak anodic current (Ipa) from 43 μA to 104 μA. The sensor …

The Pre-Polarization And Concentration Of Cells Near Micro-Electrodes Using Ac Electric Fields Enhances The Electrical Cell Lysis In A Sessile Drop, Kishor Kaphle, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Cell lysis is the starting step of many biomedical assays. Electric field-based cell lysis is widely used in many applications, including point-of-care (POC) applications, because it provides an easy one-step solution. Many electric field-based lysis methods utilize micro-electrodes to apply short electric pulses across cells. Unfortunately, these cell lysis devices produce relatively low cell lysis efficiency as electric fields do not reach a significant portion of cells in the sample. Additionally, the utility of syringe pumps for flow cells in and out of the microfluidics channel causes cell loss and low throughput cell lysis. To address these critical issues, we …

Detecting Sars-Cov-2 In Ct Scans Using Vision Transformer And Graph Neural Network, Kamorudeen Amuda, Almustapha Wakili, Tomilade Amoo, Lukman Agbetu, Qianlong Wang, Jinjuan Feng

Electrical & Computer Engineering Faculty Publications

The COVID-19 pandemic has presented significant challenges to global healthcare, bringing out the urgent need for reliable diagnostic tools. Computed Tomography (CT) scans have proven instrumental in detecting COVID-19-induced lung abnormalities. This study introduces Convolutional Neural Network, Graph Neural Network, and Vision Transformer (ViTGNN), an advanced hybrid model designed to enhance SARS-CoV-2 detection by combining Graph Neural Networks (GNNs) for feature extraction with Vision Transformers (ViTs) for classification. Using the strength of CNN and GNN to capture complex relational structures and the ViT capacity to classify global contexts, ViTGNN achieves a comprehensive representation of CT scan data. The model was …

Adaptive Fusion Neural Networks For Sparse-Angle X-Ray 3d Reconstruction, Shaoyong Hong, Bo Yang, Yan Chen, Hao Quan, Shan Liu, Minyi Tang, Jiawei Tian

Electrical & Computer Engineering Faculty Publications

3D medical image reconstruction has significantly enhanced diagnostic accuracy, yet the reliance on densely sampled projection data remains a major limitation in clinical practice. Sparse-angle X-ray imaging, though safer and faster, poses challenges for accurate volumetric reconstruction due to limited spatial information. This study proposes a 3D reconstruction neural network based on adaptive weight fusion (AdapFusionNet) to achieve high-quality 3D medical image reconstruction from sparse-angle X-ray images. To address the issue of spatial inconsistency in multi-angle image reconstruction, an innovative adaptive fusion module was designed to score initial reconstruction results during the inference stage and perform weighted fusion, thereby improving …

High-Fidelity Soh Prediction In Lithium-Ion Batteries Using Hybrid Ml Networks, Shafiyee Islam, Gon Namkoong

Electrical & Computer Engineering Faculty Publications

Accurate and efficient prediction of lithium-ion battery state of health (SOH) is critical for ensuring reliability in electric vehicles, grid storage, and aerospace systems. Traditional SOH estimation methods often struggle with nonlinear degradation behaviors and lack sensitivity to subtle electrochemical signals, limiting their real-world deployment. To address these challenges, this study examines hybrid deep learning models that integrate differential capacity (dQ/dV) analysis to enhance predictive accuracy. Four hybrid architectures - hybrid CNN-LSTM multihead, CNN extractor for LSTM, DNN-LSTM, and DNN Bi-LSTM - were developed and evaluated using the NASA randomized battery usage dataset, offering a realistic benchmark under diverse operational …

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 …

Development Of 2d Microfluidics Surface With Low-Frequency Electric Fields For Cell Separation Applications, Madushan Wickramasinghe, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Cell separation techniques are widely used in many biomedical and clinical applications for the development of screening, diagnosis and therapeutic tests. Current 3D microfluidics-based cell separation methods have limited applications in part due to low throughput and technical complexity. To address these critical needs, we have developed a 2D microfluidics surface which is the miniaturized version of a 3D microfluids cell separation device. Using low-frequency electric fields (1–10 Vpp and 1 kHz–20 MHz), we have first studied dielectrophoresis, AC electro-osmosis and capillary flow within a sessile drop, and finally utilized the results to develop the 2D cell separation surface. Our …

Enhancing Channel Data Savings And Information Transfer Efficiency In Ultrasound Imaging, Sai Konda, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

Ultrasound is a popular imaging technique mainly due to its non-invasive nature. And so, it is being used in a variety of applications. Due to plane wave imaging technique in ultrasound, frame rate of ultrasound imaging has the potential for being very high. Due to which, many channel data frames are being generated within a few seconds. As a result, tasks such as storing data frames and transferring them from front end ultrasonic system to processing computers are presenting significant challenges. Our current research work minimized these issues. We proposed and implemented: (a) Data encoding technique - We combined every …

Delivery Of Medical Supplies To Remote Locations Via Unmanned Aerial Vehicles: Approaches, Challenges, And Solutions, Meshari Aljohani, Ravi Mukkamala, Stephanie Olariu

Computer Science Faculty Publications

Unmanned Aerial Vehicles (UAVs) are becoming more important in improving healthcare logistics, in particular due to their cost effectiveness, minimized risk, and versatile operational capabilities. This study explores the deployment of autonomous UAVs to deliver medical supplies to remote areas. Advances in ledger technology, smart contracts, and machine learning have transformed tasks previously managed by human teams or manually controlled UAVs into fully autonomous missions. We present a comprehensive analysis of the challenges and initial solutions vital for the effective use of autonomous UAVs in the delivery of medical supplies. In addition, we propose a machine-learning model to optimize UAV …

Evaluation Of The Dnazyme Gr5 For The Determination Of Lead Speciation In Natural Waters, Gaganprit Gill

Theses and Dissertations (Comprehensive)

This thesis explores the development and application of a DNAzyme-based biosensor designed to detect labile metal species in environmental samples. Real time and on-site monitoring of labile metal fractions would make a valuable contribution to environmental management, as these fractions are the most bioavailable and pose significant toxicity risks to aquatic organisms. Conventional methods for detecting labile metals, while effective, are often burdened by high costs, complexity, and lengthy processing times, making them less ideal for rapid and widespread environmental assessments.

The first manuscript of this thesis (chapter 2) establishes the fundamental capabilities of the Pb²⁺-specific DNAzyme GR5 …

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 …

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.

Characterizing Biomolecular Structure Features Through An Innovative Elliptical Dichroism Spectrometry For Cancer Detection, Yusuf Asad, Keerthi Priya Jangili, Amara Arshad, Maliha Elma, Komila Rasuleva, Alfred Akinlalu, Tommy Gao, Umamaheswara Rao Tida, Wenjie Xia, Dali Sun

Electrical and Computer Engineering: Faculty Scholarship

This research introduces a novel method for evaluating the structural features of biomolecules, utilizing our innovative Elliptical Dichroism (ED) spectrometer specifically designed for stereochemical analysis. By integrating ED spectrometry with autocorrelation (AC) analysis, we investigate the conformational characteristics of biological molecules such as amino acids, proteins, and extracellular vesicles (EVs) induced by elliptically polarized UV absorption. Our streamlined approach offers a cost-effective and portable solution with minimal sample consumption and supports multiple working modes to efficiently characterize biomolecular structures. The insight from this new approach demonstrates potential applications in using biomolecular characterization for cancer detection.

Multimodal Mixing Convolutional Neural Network And Transformer For Alzheimer’S Disease Recognition, Junde Chen, Yun Wang, Adnan Zeb, M. D. Suzauddola, Yuxin Wen

Engineering Faculty Articles and Research

Early recognition of Alzheimer’s disease (AD) and its precursor state, mild cognitive impairment (MCI), is pivotal in interrupting the progression of the disease and providing suitable treatment. Recent development in deep learning techniques has drawn great research attention for improving the efficacy of AD recognition. However, numerous current methods solely utilize data from a single auxiliary domain, limiting their ability to harness valuable intrinsic insights from multiple domains. To cope with the challenge, this paper is devoted to establishing an innovative multimodal medical data fusion model, termed as MMDF, to perform Alzheimer’s disease recognition. Multimodal data including clinical records and …

An International Consensus Panel On The Potential Value Of Digital Surgery, Jamie Erskine, Payam Abrishami, Jean Christophe Bernhard, Richard Charter, Richard Culbertson, Jo Carol Hiatt, Ataru Igarashi, Gretchen Purcell Jackson, Matthew Lien, Guy Maddern, Joseph Soon Yau Ng, Anita Patel, Koon Ho Rha, Prasanna Sooriakumaran, Scott Tackett, Giuseppe Turchetti, Anastasia Chalkidou

School of Public Health Faculty Publications

OBJECTIVES: The use of digital technology in surgery is increasing rapidly, with a wide array of new applications from presurgical planning to postsurgical performance assessment. Understanding the clinical and economic value of these technologies is vital for making appropriate health policy and purchasing decisions. We explore the potential value of digital technologies in surgery and produce expert consensus on how to assess this value. DESIGN: A modified Delphi and consensus conference approach was adopted. Delphi rounds were used to generate priority topics and consensus statements for discussion. SETTING AND PARTICIPANTS: An international panel of 14 experts was assembled, representing relevant …

Smart Toys For Sensing And Soothing Distress In Pediatric Patients, Jonathan Daniel Bonilla

Dartmouth College Master’s Theses

This thesis develops and evaluates child-centered technologies to support remote monitoring of pediatric patients, with an emphasis on childhood cancer and pediatric chronic pain. For these and many other health conditions, current therapies tend to focus on treating physical symptoms yet neglect the psycho-emotional aspects of managing the illness. However, such mental states play a major role in recovery. Research has shown that cancer patients with better mental health have better prognoses, higher possibilities of remission, and faster healing processes, while chronic pain patients with better mental health report lower levels of pain. To enable more personalized, continuous, and scalable …

Precision Medicine For Apical Lesions And Peri-Endo Combined Lesions Based On Transfer Learning Using Periapical Radiographs, Pei Yi Wu, Yi Cheng Mao, Yuan Jin Lin, Xin Hua Li, Li Tzu Ku, Kuo Chen Li, Chiung An Chen, Tsung Yi Chen, Shih Lun Chen, Wei Chen Tu, Patricia Angela R. Abu

Ateneo Laboratory for Intelligent Visual Environments

An apical lesion is caused by bacteria invading the tooth apex through caries. Periodontal disease is caused by plaque accumulation. Peri-endo combined lesions include both diseases and significantly affect dental prognosis. The lack of clear symptoms in the early stages of onset makes diagnosis challenging, and delayed treatment can lead to the spread of symptoms. Early infection detection is crucial for preventing complications. PAs used as the database were provided by Chang Gung Memorial Medical Center, Taoyuan, Taiwan, with permission from the Institutional Review Board (IRB): 02002030B0. The tooth apex image enhancement method is a new technology in PA detection. …

In-House Polydimethylsiloxane Microfluidic Device On Single Cell Trapping And Culturing Of Leukemia Cell Line: Comparison Between Conventional And Conventional With Centrifugal Methods, Alongkorn Pimpin, Sudchaya Bhanpattanakul, Tepparit Wongpakham, Chomkwan Tawatcharaporn, Thanawit Siha-Umphai, Mookdapa Sinsiriphan, Atikan Chalermchuang, Tewan Tongmanee, Attawut Thanomsridetchai, Thammawit Suwannaphan, Witsaroot Sripumkhaie, Pattaraluck Pattamang, Mayuree Chanasakulniyom, Praprudee Piyaviriyakul, Wutthinun Jeamsaksiri, Achariya Sailasuta, Theerawat Tharasanit, Theerayuth Kaewamatawong

The Thai Journal of Veterinary Medicine

To develop a suitable model to study biological and characterization of Cancer stem cells (CSCs), single cell trapping and culturing using microfluidic techniques have become a high-through put system that can manage and control microenvironment and practical intracellular analysis. The aim of this study was to develop and validate a microfluidic device for single cell trapping and culturing using the leukemia cell line as a cell model. Comparison between conventional and conventional with centrifugal methods was also analyzed. To compare trapping efficacy between these 2 methods, leukemia cell concentration of 1.5×106 cells/ml was loaded with a flow rate of 0.25 …

Evaluation Of The Alveolar Crest And Cemento-Enamel Junction In Periodontitis Using Object Detection On Periapical Radiographs, Tai Jung Lin, Yi Cheng Mao, Yuan Jin Lin, Chin Hao Liang, Yi Qing He, Yun Chen Hsu, Shih Lun Chen, Tsung Yi Chen, Chiung An Chen, Kuo Chen Li, Patricia Angela R. Abu

Ateneo Laboratory for Intelligent Visual Environments

The severity of periodontitis can be analyzed by calculating the loss of alveolar crest (ALC) level and the level of bone loss between the tooth’s bone and the cemento-enamel junction (CEJ). However, dentists need to manually mark symptoms on periapical radiographs (PAs) to assess bone loss, a process that is both time-consuming and prone to errors. This study proposes the following new method that contributes to the evaluation of disease and reduces errors. Firstly, innovative periodontitis image enhancement methods are employed to improve PA image quality. Subsequently, single teeth can be accurately extracted from PA images by object detection with …

Development Of Feature Extraction Models To Improve Image Analysis Applications In Cancer, Yu Shi

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Cancer poses a significant global health challenge. With an estimated 20 million new cases diagnosed worldwide in 2022 and 9.7 million fatalities attributable to the disease, the economic burden of cancer is immense. It impacts healthcare systems and imposes substantial costs for its care on patients and their families. Despite advancements in early detection, prevention, and treatment that have reduced overall cancer mortality rates, the growing prevalence of cancer, particularly among younger individuals, remains a pressing issue.

Recent advancements in medical imaging technology have progressed significantly with the help of emerging computer vision and artificial intelligence (AI) technology. Despite these …

Nanoparticle-Based Approaches To Brain Injury And Studies For Improved Detectability Toward Better Delivery Characterization, Hunter A. Miller

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The clinical translation of nanoparticle (NP) therapeutics for brain injury has been slow despite preclinical promise. The causes of disconnect between preclinical and clinical outcomes is multifactorial, but insufficient delivery is noteworthy. Preclinical delivery characterization often lacks, obscuring mechanisms of failure, slowing development. Multimodal imaging is a promising strategy to improve delivery characterization, combining the strengths of various modalities. Magnetic resonance imaging (MRI) and luminescence imaging are a suitable combination for multimodal imaging, expanding the spatial and temporal resolution of either alone, but further material development is needed to enhance detectability. One problem is the interference of cellular autofluorescence in …

Auxiliary Diagnosis Of Dental Calculus Based On Deep Learning And Image Enhancement By Bitewing Radiographs, Tai Jung Lin, Yen Ting Lin, Yuan Jin Lin, Ai Yun Tseng, Chien Yu Lin, Li Ting Lo, Tsung Yi Chen, Shih Lun Chen, Chiung An Chen, Kuo Chen Li, Patricia Angela R. Abu

Ateneo Laboratory for Intelligent Visual Environments

In the field of dentistry, the presence of dental calculus is a commonly encountered issue. If not addressed promptly, it has the potential to lead to gum inflammation and eventual tooth loss. Bitewing (BW) images play a crucial role by providing a comprehensive visual representation of the tooth structure, allowing dentists to examine hard-to-reach areas with precision during clinical assessments. This visual aid significantly aids in the early detection of calculus, facilitating timely interventions and improving overall outcomes for patients. This study introduces a system designed for the detection of dental calculus in BW images, leveraging the power of YOLOv8 …

Noninvasive Technique For Measuring Cardiac Output, Grace E. Kolar, Rachel Simonton, Eli Strohecker

Williams Honors College, Honors Research Projects

NA

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 …

Creating A Collapsible Sling Lift Capable Of Transporting Patients Between Various Locations, Macey Jewell Ross, Cameron Delaney Hillman, Lydia Noel Miller

Honors Theses

As Senior Biomedical Engineering students at the University of Mississippi, we, Lainey Hillman, Lydia Miller, and Macey Ross, are required to complete a final senior capstone for our department. This project aims to provide a solution to a current unmet clinical need in the healthcare industry, thus our team sought to improve the lack of transportability of sling lifts. The current sling lifts on the market display numerous issues: heavy, bulky, use confined to certain areas, and use specific for only one type of transportation. To combat these problems, we designed a sling lift that was lightweight, collapsible, safe, and …

Towards A Wearable Device For Measuring Impedance Plethysmography Of The Radial Artery, Pritom Chowdhury

Dartmouth College Master’s Theses

Recent advancements in bioimpedance technology have demonstrated significant promise in the application of cardiac health monitoring. This research explores the design and development of a forearm-based wearable bioimpedance device for non-invasive measurement of heart rate and respiratory rate at an accuracy level comparable to medical-grade monitors. It utilizes a tetrapolar electrode configuration to analyze bioimpedance changes in the radial artery due to blood flow.

An ongoing aspect of this work involves the preliminary development of an embedded framework intended to integrate signal generation, acquisition, and processing within the device to achieve compact and efficient system design, anticipated to contribute to …