Biomedical Commons^™

2-Channel Eeg Neurofeedback System, Tim Erwin, Donna Nikjou, Sebastian Turkewitz

Electrical Engineering

This work describes the design of an EEG-based neurofeedback system which provides users with real-time feedback on their level of focus or relaxation. By analyzing the spectral content of the brain activity measured via scalp electrodes, focus and relaxation levels can be quantified. Based on these measurements, live feedback in the form of moving bar graphs is provided to users, allowing them to gain awareness of their mental-state and more efficiently learn how to consciously relax or focus. This project covers the design of the system, including amplification and filtering stages, digitization, and signal processing. The system interfaces with a …

Generative Data Augmentation: Using Dcgan To Expand Training Datasets For Chest X-Ray Pneumonia Detection, Ryan D. Maier

Master's Theses

Recent advancements in computer vision have demonstrated remarkable success in image classification tasks, particularly when provided with an ample supply of accurately labeled images for training. These techniques have also exhibited significant potential in revolutionizing computer-aided medical diagnosis by enabling the segmentation and classification of medical images, leveraging Convolutional Neural Networks (CNNs) and similar models. However, the integration of such technologies into clinical practice faces notable challenges. Chief among these is the obstacle of acquiring high-quality medical imaging data for training purposes. Patient privacy concerns often hinder researchers from accessing large datasets, while less common medical conditions pose additional hurdles …

3d Automated Surgeon’S Hand Motion Assessment Using A Cascade Fuzzy Supervisor During Intelligent Box-Trainer System Skills Training In A Multi-Thread Video Processing, Fatemeh Rashidi Fathabadi

Dissertations

For certain surgical procedures, Minimally Invasive Surgery (MIS) has become more advantageous than traditional open surgery. Therefore, mastery of laparoscopic skills is an essential component of surgical training and requires considerable time and effort. The Fundamentals of Laparoscopic Surgery (FLS) program has been developed as a tool to improve and assess fundamental surgical skills. In fact, using a low-cost Box-Trainer or a simulator, laparoscopic surgeons are required to train using a set of structured tasks that can be objectively used to assess their laparoscopic skills, which must be mastered before carrying out real-life laparoscopic procedures. These tasks include peg transfer, …

Providing Cadence Feedback In Real-Time To Guide Cardiovascular Workouts, Levi O. Rash

Master's Theses

Cardiovascular workouts offer numerous health benefits, yet beginners often find it challenging to initiate them. Existing wearable technologies, although providing valuable feedback such as heart rate zones, often disrupt the workout flow and distract users due to the need for interaction with the wearable display. In response, we propose an alternative feedback mechanism: cadence, measured in steps per minute. This feedback mechanism uses multiplicative control to produce the correct cadence for the user’s target heart rate (HR). To model the HR and cadence relationship, a first-order system was used. The prototype implementation of this system was completed in Arduino, using …

Affordable Bioprint Head-Adapter For 3d Printers, Andrew Ceralde, Dominic Drake, Noah Engles, Mohammad Alwan, Nevada Perry

Honors Capstones

Introduction: Addressing the need for affordable and accessible bioprinting technology, the Northern Illinois University bioprinting research and design project aims to democratize the field by developing an open source bioprint head. The initiative targets the prohibitive cost of commercial bioprinters by proposing an optimal design that can be integrated with widely available 3D printers, like the Creality Ender-3. This approach seeks to enable the widespread adoption of bioprinting technology, particularly for applications in tissue engineering and regenerative medicine.

Methods: Leveraging SolidWorks for design, the project employs a methodology that combines a precision extrusion system with thermal and UV crosslinking capabilities. …

The Contribution Of Micrornas To Rybp Silencing In Glioblastoma Multiforme, Alex B. Lee

Graduate Theses

Glioblastoma multiforme (GBM) is a highly aggressive and invasive tumor of the central nervous system (CNS). Survival rates are abysmal, with only 7.2% of patients alive 5-years after diagnosis. Because of this, understanding epigenetic alterations that give GBM tumors their aggressive phenotypes is critical for the development of more targeted and effective therapies. These alterations frequently affect a group of proteins called the Polycomb group proteins, which play important oncogenic and tumor suppressive roles in cancer. One Polycomb protein, the RING1- and YY1-binding protein (RYBP), is downregulated in a majority of GBM patients, suggesting a strong tumor suppressive property. In …

Effect Of Patient Specific Blood Biomarkers On Nanoparticle - Cell Interactions, Veronica Gabriela Contreras

Open Access Theses & Dissertations

Nanoparticles are currently known to be a promising material class for bio-applications in drug delivery and vaccine development. Using gold nanoparticles of varied sizes, in this case 45 and 100 nanometers as a model nanomaterial system, we investigated how patients' blood physiology and chemistry (such as solute, protein, lipid levels) affect the biological response to bionanomaterials. When nanoparticles are injected into the body, biomolecules in the blood adsorb to the nanoparticle's surface to form a biomolecular corona that is specific to the patient's unique blood composition. This biomolecular corona is important because it affects the in vivo fate and biodistribution …

Bcl2 Mediated Targeted Drug Delivery For The Treatment Of Kidney Fibrosis And Stomach Cancer, Humayra Afrin

Open Access Theses & Dissertations

Apoptosis, the programmed death of cells, is primarily regulated by a delicate balance between pro-apoptotic and anti-apoptotic signals. The Bcl-2 (B-cell lymphoma 2) family of proteins acts as anti-apoptotic agents, promoting cell survival. Dysregulation of these proteins is a common occurrence in conditions such as cancer and fibrosis, where overexpression of anti-apoptotic members can foster tumor cell survival and fibroblast activation. In this study, our aim was to explore the therapeutic potential of Bcl-2 inhibitors, both as a small molecule (specifically Navitoclax (Navi)), inhibitor and as Bcl-2 siRNA, for targeted treatment. Intravenous administration of Navi often leads to thrombocytopenia, necessitating …

Biofabrication Of Human Tissue-On-A-Chip Models Using Engineered Biocompatible Electrospun Scaffolds, Zayra Naomi Dorado

Open Access Theses & Dissertations

This study explored the adoption of furfuryl gelatin (F-gelatin) based electrospun scaffolds compared with poly-caprolactone (PCL) as promising biomaterials for tissue engineering applications. Tissue-on-a-chip models, incorporating F-gelatin and PCL electrospun scaffolds, offer promising avenues for healthy and disease-in-vitro tissue models that can be explored to investigate underlying physiological mechanisms involved in disease development. Previous research has demonstrated the cytocompatibility of F-gelatin when used for modifying implant surfaces and tissue repair applications [1]. Our earlier published works have also successfully utilized F-gelatin for in-vitro cardiac tissue engineering [2][3]. We designed F-gelatin and PCL electrospun scaffolds to replicate the native tissue extracellular …

Selective Transfection Of A Transferrin Receptor-Expressing Cell Line With Dna-Lipid Nanoparticles And Synthesis Of Parasite-Derived Glycans As Biomarkers For Leishmaniasis, Irodiel Vinales Lozano

Open Access Theses & Dissertations

Despite notable progress in lipid nanoparticle (LNP)-mediated gene delivery, achieving selective transfection of specific cell types, such as cancer cells, remains a significant hurdle, hindering the advancement of innovative gene therapies. In this study, we engineered an LNP formulation encapsulating plasmid DNA (pDNA) encoding the monomeric Green Lantern (mGL) fluorescent reporter protein. The DT7 peptide ligand targeting human transferrin receptor 1 (hTfR1) was also conjugated to the LNP surface for targeted delivery to hTfR1-expressing cells. Optimization of LNP composition yielded favorable particle diameter, ζ-potential, yield, and pDNA encapsulation efficiency. Evaluation of transfection selectivity using a panel of two engineered cell …

Hand Movement Analysis For Surgical Suturing Skill Assessment, Amir Mehdi Shayan

All Theses

To enhance patient safety, surgical education is increasingly incorporating simulation for formative skills assessment and training. However, many standardized assessment tools rely on human raters for performance assessment, which is resource-intensive and subjective. Simulators that provide automated and objective metrics from sensor data can address this limitation. This thesis presents an instrumented bench suturing simulator, patterned after the Clock Face (CF) radial suturing model from the Fundamentals of Vascular Surgery (FVS), for automated and objective assessment of open suturing skills by particularly focusing on biomechanical analysis of hand movements. For this research, 97 participants (35 attending surgeons and fellows, 32 …

Characterizing The Molecular And Cellular Changes Of Senescent Cells Induced By Diverse Stressors In 2d And 3d Microenvironments, Apoorva Chauhan

UNLV Theses, Dissertations, Professional Papers, and Capstones

Aging is a risk factor for myriad diseases and is often associated with the accumulation of senescent cells. Cellular senescence, a process of irreversible cell cycle arrest, is associated with various changes in cellular morphology and function. While senescence will occur naturally in a time-dependent manner, it can be prematurely induced by various extrinsic and intrinsic factors. Most senescence studies model cell behavior in two-dimensional (2D) microenvironments; however, these models are not physiologically relevant. In this study, the effects of naturally occurring reactive oxygen species (ROS) hydrogen peroxide (H2O2) and commonly used chemotherapy drugs, doxorubicin and palbociclib, on cellular senescence …

Low Impedance, Durable, Self-Adhesive Hydrogel Epidermal Electrodes For Electrophysiology Recording, Naiyan Wu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Traditional electrodes used for electrophysiology recording, characterized by their hard, dry, and inanimate nature, are fundamentally mismatched with the soft, moist, and bioactive characteristics of biological tissues, leading to suboptimal skin-electrode interfaces. Hydrogel materials, mirroring the high water content and biocompatibility of biological tissues, emerge as promising candidates for epidermal electronic materials due to their adjustable physicochemical properties. However, challenges such as inadequate electrical conductivity, elevated skin impedance, unreliable adhesion in moist conditions, and performance decline from dehydration have significantly restricted the efficacy and applicability of hydrogel-based electrodes. In this thesis, we report a high-performance hydrogel epidermal electrode patch for …

Advancing Brain Tumor Segmentation With Spectral–Spatial Graph Neural Networks, Sina Mohammadi, Mohamed Allali

Engineering Faculty Articles and Research

In the field of brain tumor segmentation, accurately capturing the complexities of tumor sub-regions poses significant challenges. Traditional segmentation methods usually fail to accurately segment tumor subregions. This research introduces a novel solution employing Graph Neural Networks (GNNs), enriched with spectral and spatial insight. In the supervoxel creation phase, we explored methods like VCCS, SLIC, Watershed, Meanshift, and Felzenszwalb–Huttenlocher, evaluating their performance based on homogeneity, moment of inertia, and uniformity in shape and size. After creating supervoxels, we represented 3D MRI images as a graph structure. In this study, we combined Spatial and Spectral GNNs to capture both local 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 …

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 …

The Sensory Accommodation Framework For Technology: Bridging Sensory Processing To Social Cognition, Louanne Boyd

Engineering Faculty Books and Book Chapters

This book provides a thorough introduction to the many facets of designing technologies for autism, with a particular focus on optimizing visual attention frameworks. This book is designed to provide a detailed overview of several aspects of technology for autism. Each Chapter illustrates different parts of the Sensory Accommodation Framework and provides examples of relevant available technologies. The books first discusses a variety of skills that make up human development as well as a history of autism as a diagnosis and the birth of the neurodiversity movement. It goes on to detail individual types of therapy and how they interact …

Energy Harvesting Face Mask Using A Thermoelectric Generator For Powering Wearable Health Monitoring Sensors, Ugur Erturun, Cansu Yalim, James E. West

Engineering Management & Systems Engineering Faculty Publications

A wearable energy harvester (EH) incorporating a face mask with a thermoelectric generator is demonstrated. The function of this device is to generate electrical power from the heat produced by the human body, particularly breath, with the specific aim of powering wearable sensor applications. A prototype was built using a commercially available N95 face mask, a thermoelectric generator, and a heatsink. The performance of this EH device was assessed using experimental and numerical methodologies. The experimentally tested power output of the prototype was found to be ≈100 µW, with a corresponding power density of ≈30 µW/cm3, for a temperature difference …

Multi-Magnetic Material Transcranial Magnetic Stimulation Coils Development And Electric Field Measurement & Modeling Using Machine Learning, Mohannad Tashli

Theses and Dissertations

Transcranial Magnetic Stimulation (TMS) is a safe, effective, and non-invasive therapy for treating several psychiatric and neurological disorders. TMS is Food and Drug Administration (FDA) approved treatment and is commonly applied to patients who do not respond to medications for the treatment of clinical depression, smoking cessation, obsessive-compulsive disorder and migraine. Recently, there has been an increase in the development of electromagnetic neuromodulation techniques targeted at enhancing the effectiveness of TMS devices for the treatment of mental diseases. In TMS stimulation, focality is an important factor which determines the specificity of the pulses induced in different brain tissues. The electromagnetic …

Cleaning And Characterization Of Chemical Vapor Deposited Graphene For Nanoelectronic Device Development, Sakib Ishraq

Graduate Theses, Dissertations, and Problem Reports (ETD)

Nanoelectronic devices based on graphene are a promising technology that combines the sensitivity and specificity of ion and element recognition with the accuracy and precision of electronics. The detection principle is based on the interaction of the target molecules with the nanodevice surface, which generates a measurable electrical signal. In the current study, graphene and its derivatives, synthesis and fabrication of high quality, good uniformity, and low defects graphene have been investigated as they are critical for high-performance and highly sensitive devices. Among many synthesis methods, chemical vapor deposition (CVD), have been used that needs to be transferred from the …

Non-Invasive Monitoring Device For Early Detection Of Breast Cancer Related Lymphedema, Amy Prendergast

Honors Theses and Capstones

Breast Cancer Related Lymphedema (BCRL) is a common co-morbidity in cancer survivors following neoadjuvant therapies such as chemotherapy, radiation, and/or surgery. It is brought about by the disruption in the lymphatic system (think lymph node biopsy) that leads to a buildup of lymphatic fluid in the arm. Current diagnostic strategies for this condition are merely retroactive, and fairly limited in the parameters that are examined to ensure patient well-being long term. We hypothesize that with an approach that mimics bioimpedance spectroscopy analysis, we will be able to provide a clinical support tool that would better determine early stages of lymphedema …

An Fpga-Based Eit System For Deep Space Medical Imaging, Kendall R. Farnham

Dartmouth College Ph.D Dissertations

Dangers associated with high radiation and microgravity exposure in space are critical challenges inhibiting us from exploring deep space and pursuing long-duration missions, as current medical systems are unable to monitor, diagnose, or treat tissue injury within physical spacecraft constraints and communication limits. Ultrasound (US) is the current imaging system used on the International Space Station, but this technology relies on telemedical support (or onboard artificial intelligence/autonomous capabilities) for both operation and diagnosis, posing challenges for crews isolated in deep space. Electrical impedance tomography (EIT) is a non-invasive, non-ionizing technology that produces images of the electrical properties of tissues and …

Implementing Associative Learning Using Neuromorphic Robot, Vinay Kumar Pillalamarri

Dissertations, Master's Theses and Master's Reports

Associative learning, a key cognitive process seen across the animal kingdom, enables organisms to form connections between stimuli and adapt their behaviors based on past experiences. A particularly powerful example is fear conditioning, where animals learn to associate a neutral stimulus with an aversive one, allowing them to predict and avoid potential threats. Inspired by this mechanism, this project implements associative learning on an unmanned ground vehicle (UGV) to develop adaptive behavior through neuromorphic principles. Utilizing Nengo for neural modeling, the UGV learns to associate visual (red color) and tactile (vibration) stimuli through Hebbian learning, a biologically inspired synaptic adaptation …

Wavelet-Based Harmonization Of Local And Global Model Shifts In Federated Learning For Histopathological Images, W. Farzana, A. Temtam, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Federated Learning (FL) is a promising machine learning approach for development of data-driven global model using collaborative local models across multiple local institutions. However, the heterogeneity of medical imaging data is one of the challenges within FL. This heterogeneity is caused by the variation in imaging scanner protocols across institutions, which may result in weight shift among local models leading to deterioration in predictive accuracy of global model. The prevailing approaches involve applying different FL averaging techniques to enhance the performance of the global model, ignoring the distinct imaging features of the local domain. In this work, we address both …

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 …

Adversarial Training Based Domain Adaptation Of Skin Cancer Images, Syed Qasim Gilani, Muhammad Umair, Maryam Naqvi, Oge Marques, Hee-Cheol Kim

Electrical & Computer Engineering Faculty Publications

Skin lesion datasets used in the research are highly imbalanced; Generative Adversarial Networks can generate synthetic skin lesion images to solve the class imbalance problem, but it can result in bias and domain shift. Domain shifts in skin lesion datasets can also occur if different instruments or imaging resolutions are used to capture skin lesion images. The deep learning models may not perform well in the presence of bias and domain shift in skin lesion datasets. This work presents a domain adaptation algorithm-based methodology for mitigating the effects of domain shift and bias in skin lesion datasets. Six experiments were …

Domain Adaptive Federated Learning For Multi-Institution Molecular Mutation Prediction And Bias Identification, W. Farzana, M. A. Witherow, I. Longoria, M. S. Sadique, A. Temtam, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Deep learning models have shown potential in medical image analysis tasks. However, training a generalized deep learning model requires huge amounts of patient data that is usually gathered from multiple institutions which may raise privacy concerns. Federated learning (FL) provides an alternative to sharing data across institutions. Nonetheless, FL is susceptible to a few challenges including inversion attacks on model weights, heterogenous data distributions, and bias. This study addresses heterogeneity and bias issues for multi-institution patient data by proposing domain adaptive FL modeling using several radiomics (volume, fractal, texture) features for O6-methylguanine-DNA methyltransferase (MGMT) classification across multiple institutions. The proposed …

Distance Estimation Based On Step Frequency Using Accelerometer Data, Rami M. Al-Naimat, Khawlah M. Harahsheh, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

In recent years, smartphone sensors have become one of the most important and easily available sensors to facilitate people's lives, especially in health care and positioning (indoor environments). However, the data coming from smartphone sensors can be distorted during the user’s movement such as irrelevant movements, walk mode, and speed of walking. This distortion (noise) impairs the estimated distance accuracy (accumulative error) which increases with increasing walking distance. In addition, the accuracy of the distance traveled is affected by the user's speed, as the speed affects the step length. This work proposes a novel approach for calculating step length in …

Investigation Of Delta-Focused Ictal Electrical Source Imaging In Refractory Focal Epilepsy, Jared A. Rybarczyk

Theses and Dissertations--Electrical and Computer Engineering

Refractory focal epilepsy is characterized by the presence of seizures that cannot be controlled via anti-seizure medications. For patients suffering from this form of epilepsy, accurate identification of the seizure onset zone is a crucial step for many modalities of treatment. Electrical source imaging (ESI) allows for estimation of the seizure onset zone from electroencephalography. EEG feature extraction is an important step that can impact the final accuracy of source estimates. This work provides a review of 23 ictal ESI studies and proposes a delta-focused ictal ESI methodology. Our proposed delta-focused ictal ESI is implemented across 33 refractory focal epilepsy …

Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso

Theses and Dissertations--Electrical and Computer Engineering

The emergence of deep learning models and their success in visual object recognition have fueled the medical imaging community's interest in integrating these algorithms to improve medical diagnosis. However, natural images, which have been the main focus of deep learning models and mammograms, exhibit fundamental differences. First, breast tissue abnormalities are often smaller than salient objects in natural images. Second, breast images have significantly higher resolutions but are generally heavily downsampled to fit these images to deep learning models. Models that handle high-resolution mammograms require many exams and complex architectures. Additionally, spatially resizing mammograms leads to losing discriminative details essential …