Biomedical Commons^™

Comparative Analysis Of Takagi-Sugeno And Mamdani Fuzzy Inference Architectures With Anfis-Based Automated Rule Generation For Eeg-Based Cognitive State Monitoring, Amina Radončić, Mehrija Hasičić, Jasmin Kevrić

Communications of the IIMA

Fuzzy inference systems have demonstrated considerable promise for EEG-based cognitive state monitoring in neurodegenerative conditions. However, two design decisions significantly influence system performance and clinical applicability: the choice of inference architecture (Takagi-Sugeno vs Mamdani) and the method of rule and membership function generation (manual expert-driven vs data-driven automated). This paper presents a comparative analysis of both dimensions in the context of an EEG-based Alzheimer’s disease monitoring system operating on the ds004504 OpenNeuro dataset (88 subjects: 36 AD, 23 FTD, 29 HC). A Takagi-Sugeno system, implemented as a hybrid FSM-Fuzzy architecture, is compared against a Mamdani equivalent across four axes: inference …

Familybloom: Examining Ecologies Of Collaboration In Family-Centered Health Tracking, Lucas M. Silva, Aehong Min, Evropi Stefanidi, Franceli L. Cibrian, Jesus A. Beltran, Cassie Zeiler, Sabrina E. B. Schuck, Kimberley D. Lakes, Gillian R. Hayes, Daniel A. Epstein

Engineering Faculty Articles and Research

Family health informatics tools can help support well-being with shared data tracking. Prior work typically focused on shared data review, but often in specific moments, like bedtime, or centered on caregiving of children or elderly members. To investigate how tracking can support mutual health collaboration between family members pervasively across daily contexts, we designed and deployed FamilyBloom, a glanceable smartwatch and home display system for mood and goal tracking. Twelve families with both neurotypical and ADHD members used FamilyBloom for three months on average. Our findings reveal how family-centered tracking created collaboration opportunities and tensions across multiple ecological systems: individual …

Consensus And Controversies Of International Guidelines For The Diagnosis, Surveillance, And Management Of Fetal Growth Restriction: An Updated Comparison, Daniele Diane Mascio, Suneet P. Chauhan, Tullio Ghi, Asma Khalil, Juliana G. Martins, Sara Sorrenti, Tamara Stampalija, Fabrizio Zullo, Francesc Figueras

Department of Obstetrics & Gynecology Faculty Publications

OBJECTIVE: To compare areas of consensus and disagreements across contemporary international and national guidelines on the diagnosis, surveillance, and management of fetal growth restriction (FGR).

DATA SOURCES: Electronic searches of MEDLINE from database inception up to March 2026 using MeSH terms and keywords related to FGR and guidelines. STUDY ELIGIBILITY CRITERIA: Critical, structured comparison of national or international guidelines on FGR published since 2010. Final inclusion required unanimous agreement from all authors.

STUDY APPRAISAL AND SYNTHESIS METHODS: Pre-specified extraction across domains: definition; prediction/prevention; surveillance tools and frequency; delivery timing and mode; and labor induction methods. Dual data …

C. Difficile Detection Method For First Responder Glove Application, Alli N. Senedak

Williams Honors College, Honors Research Projects

Clostridioides Difficile (C. diff) is a Anaerobic Gram-positive bacillus that is capable of spore formation, making it difficult to control its spread and duration in clinical environments. This phenomenon can provide danger to first responders, healthcare workers, and patients. The goal of this project is to create a biosensor capable of detecting C. diff in a clinical setting that can be applied to a glove apparatus. The project will involve the use of C. diff aptamers activated on the surface of an electrode. Once surface activation has been verified via surface analysis, the electrodes will be exposed to C. diff …

Beyond The Square Pulse: Waveform Shape, Eeg Correlates, And The Pursuit Of Natural Sensation In Tens, Jason Whitson

Honors Undergraduate Theses

This study investigates the relationship between electrical stimulus characteristics of shape and charge on evoked sensations and electroencephalogram (EEG) data during multi-waveform transcutaneous electrical nerve stimulation (TENS) of the median nerve. Neuromodulation methods have traditionally had little control over the location and quality of their associated evoked sensation (e.g., electric, vibration, touch). This experiment utilized five unique stimulus waveforms during TENS stimulation. EEG data were collected concurrently to provide an introductory objective measure of the neural responses underlying these sensory changes. Eleven participants completed three tasks (thresholding, super-threshold stimulation, two-alternative forced choice) using a two-electrode TENS approach. Stimulus waveforms were …

Healthcare Digital Twins: A Methodological Literature Review On Integrating Iot And Ai For Personalized Medicine And Predictive Care, Sara Shahnazinia, Mahsa Tavasoli, Abdolhossein Sarrafzadeh, Ali Karimoddini

Electrical & Computer Engineering Faculty Publications

Digital Twin (DT) technology has the potential to revolutionize healthcare delivery and enhance patient outcomes through personalized and precision medicine, simulation models for operations and interventions, and drug discovery. However, successful implementation of DTs in Internet of Things (IoT) and artificial intelligence (AI) healthcare is contingent upon addressing key challenges such as privacy, ethics, and robust data security. This paper presents a methodological literature review of DT applications in healthcare, systematically analyzing the current state of research, key enabling technologies, and implementation challenges. The review summarizes DT categorization approaches (application-based, technology-based, and real-time function-based); delineates core DT components such as …

Capacity, Allocation And Update Dynamics Of Human Memory Systems, Shaoying Wang

Electronic Theses and Dissertations

Information is encoded and stored in three types of memory: sensory memory (SM), short-term memory (STM), and long-term memory (LTM). SM has a large capacity but retains information for only a brief period. When information transfers to STM, only a limited amount can be stored. Information in STM can then be transferred to LTM, which has a much larger capacity and longer retention time. STM is often conceptualized as working memory (WM) to highlight its role in active information processing. Due to the limited capacity of STM, it is commonly believed that STM serves as the bottleneck for information processing. …

Non-Invasive Way For Detection Of Neonatal Jaundice Using Gbr, Priti V. Bhagat, Mukesh Raghuwanshi, Ashutosh D. Bagde

Chulalongkorn Medical Journal

Background: Neonatal jaundice is a common condition in newborns due to excess levels of bilirubin. The traditional method for bilirubin testing is invasive, i.e., through blood tests only, which is painful to infants. Therefore, this study uses machine learning algorithms to develop a non-invasive way to detect neonatal jaundice.

Objectives: Design a computer-aided support system to detect neonatal jaundice using machine learning algorithm.

Methods: The gradient-boosting regression model is used to predict the bilirubin level. Gradient Boosting is a robust boosting algorithm that combines several weak learners into strong learners, in which each new model is trained to minimize the …

Developing Deep Learning Methods For Cognitive Impairment Detection Based On Non-Invasive Data, Muath Alsuhaibani

Electronic Theses and Dissertations

Cognitive impairment detection is on the rise to help reduce the burden of healthcare costs on institutions and individuals. Mild Cognitive Impairment (MCI) is an early stage of cognitive decline progressing to Alzheimer’s disease (AD) or AD-related Dementia (ADRD). Detecting the early stages of AD/ADRD is crucial for early interventions among older adults to mitigate cognitive decline over time. However, the current diagnostic methods are often costly and/or invasive, such as MRI and PET scans. Thus, the search for non-invasive and cost-effective screening tools for the early detection of cognitive impairment using speech, language, visual, and motor data is growing. …

Study Of Ai Applications In Biomedical Data Acquisition, Communication, And Analysis: Cest Mri Acceleration And Ecg Transmissions, Adarsha Bhattarai

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

This dissertation investigates the application of artificial intelligence in biomedical data acquisition, communication, and analysis to advance neurological research and to enable the early detection of cardiovascular conditions. Despite significant advances in imaging and physiological modalities, challenges persist. Imaging modalities, such as the chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) technique are challenged by a prolonged data acquisition time and high operational costs. In addition, physiological modalities such as electrocardiogram (ECG) sensors face constraints in providing uninterrupted signal monitoring which is crucial for the timely detection of premature cardiac abnormalities. The primary goal of this work is to …

The Interplay Of Accommodation And Oculomotor Vergence Within Young Adults With Binocularly Normal Vision And Typically-Occurring Convergence Insufficiency, Sebastian Fine

Dissertations

Concerted binocular coordination evoking oculomotor and refractive responses to visual stimuli are essential to daily function. Oculomotor dysfunctions can inhibit binocular responses to visually-near stimuli and have high comorbidities to accommodative dysfunctions. Three visual cues for inward (convergent) and outward (divergent) oculomotor movements, when presented concertedly create natural-viewing conditions: disparity- the binocular difference in light cast onto the fovea due to differing ocular perspectives, blur- the acuity of a visual target which stimulates accommodation, and proximal- the perceived distance of a visual stimuli based on size.

This study aims to quantitatively investigate oculomotor vergence and accommodation performances between individuals with …

Toward The Application Of Natural Language Processing In Electronic Health Record Analysis For Taxonomy Development, Latoya Mcdonald

All Dissertations

Electronic health records (EHRs) are pivotal resources for nurse practice because they increase the timeliness and reliability of patient information at the point of care and support access by multiple healthcare providers and the individual patients themselves. However, it is widely recognized that data extraction from EHRs is challenging due to the variability in the language used in clinical care notes and the lack of standardized terminology across healthcare systems. The broad objective of this dissertation is to develop taxonomy-based classification models for nursing care by applying feature engineering approaches to EHRs that include nursing care of ostomy patients following …

Role Of Eye-Tracking Technology And Software Algorithms In Enhancing Adhd Detection And Diagnosis: A Systematic Literature Review, Lauren E. Perkins

Honors College Theses

This systematic literature review explores the role of eye-tracking technology and software algorithms in enhancing the detection and diagnosis of ADHD. ADHD, a neurodevelopmental disorder affecting both children and adults, is traditionally diagnosed through behavioral assessments, which may lack objectivity. Recent studies suggest that eye-tracking, specifically focusing on saccades, fixations, and blink rates, offers the potential for more accurate and objective measures of ADHD. The review examines clinical trials, observational studies, and machine learning research to assess the correlation between ADHD and eye movement patterns. Results indicate that individuals with ADHD exhibit distinct eye movement patterns, which can be quantified …

Cochlear Electrode Insertion Training Model, Sarah Powell, Kaelyn E. Kraley, Nathan J. Smith

Williams Honors College, Honors Research Projects

Cochlear implant surgery is a delicate procedure performed by Otolaryngologists (ENTs) to implant an electronic device into the inner ear to provide a sense of sound for people who are profoundly deaf or hard of hearing. The current practices of training involve cadavers and 3D-printed models. Cadavers are commonly used but are expensive, single-use, and do not provide visual and haptic feedback, which are essential for medical students. 3D printed models are less commonly used and are hard to fabricate and not as realistic. If medical students are not properly trained for this delicate procedure, then risks are significantly increased …

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 …

Personalized Prediction Of Tumor Recurrence With Image-Guided Physics-Informed Computational Model In High-Grade Gliomas, Walia Farzana, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

High grade gliomas are infiltrating tumors characterized by their diffusive invasion and proliferative growth. Across and within patients heterogeneity of tumors makes it challenging to determine tumor spatial extent after surgical resection. Traditionally, tumor growth predictions after surgical resections rely on generalized models and population-based observations, which do not account for individual patient differences. To address this gap, we propose a personalized approach with image-guided computational model (digital twin) that incorporates physics-based modeling to predict tumor recurrence. Our digital twin involves an inverse modeling step, followed by a recurrence model that accounts for varying surgical effects. The physics-guided inverse model …

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 …

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 …

Novel Micro-And Nanoformulations Of Paclitaxel For Targeting Metastatic Breast, Non-Small Cell Lung, And Pancreatic Cancers, Lobat Tayebi, Mehran Alavi

Electrical & Computer Engineering Faculty Publications

Nonlinear pharmacokinetics resulting from high lipophilic and low oral bioavailability, and hypersensitivity reactions and hyperlipidemia caused by formulation by Cremophor EL have limited clinical effectiveness of paclitaxel (Taxol). In this way, there is the critical necessity of innovative drug delivery systems (DDSs) to mitigate severe side effects and overcome clinical limitations of paclitaxel. In recent years, various micro- and nanoformulations, specifically polymeric nanoparticles (NPs) and lipid NPs, have been presented and approved by the Food and Drug Administration (FDA). In addition, other nanoformulations, such as polymeric nanoparticles (NPs), micelles, liposomes, and mesoporous silica nanoparticles, have shown promising results in vitro …

Towards A Multimodal Approach For Assessing Adhd Hyperactivity Behaviors, Franceli L. Cibrian, Lauren Min, Vitica Arnold

Engineering Faculty Articles and Research

Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent childhood psychiatric condition that needs an assessment of inattention, hyperactivity, and impulsiveness symptoms. Particularly in young children, hyperactivity-impulsivity stands out as a primary concern. However, those behaviors may or may not be evidenced when a child is in a small room, one-on-one with a single adult. Therefore, Ambient Intelligence technology that supports data collection in a natural setting, paired with expert human decision-making can potentially improve the quality of assessments. In this paper, we conduct a literature review and analysis to align ADHD assessment criteria with potential sensor technologies to collect …

Etherealbreathing: A Holographic Biofeedback Game To Support Relaxation In Autistic Children, Arturo Morales Téllez, Isabel López Hurtado, Franceli L. Cibrian, Monica Tentori

Engineering Faculty Articles and Research

Biofeedback training for box breathing is becoming increasingly accessible due to advancements in consumer-grade breathing sensors. However, there is limited research on their design and applications for specialized populations. This study evaluates a novel biofeedback holographic game, EtherealBreathing, designed to support autistic children. In EtherealBreathing, children practice box breathing to collect virtual elements to maintain the Earth's balance, using a wearable sensor to measure chest expansion for breath detection. A deployment study with 20 autistic children revealed that EtherealBreathing effectively promotes box breathing, leading to better health-related outcomes, such as lowering participants’ heart and respiratory rates than traditional practices. Biofeedback …

Myofibroblast Targeted Liposomes For The Treatment Of Skin Fibrosis, Elfa Beaven

Open Access Theses & Dissertations

Continuous overactivation of myofibroblasts leads to excessive deposition of profibrotic proteins, which in turn causes tissue stiffness and, ultimately, organ failure. One of those proteins, Cadherin-11 (CDH11), is reported to be overexpressed in the tissue of fibrotic skin, specifically on myofibroblasts. Similarly, chronic inflammation drives fibrosis progression in autoimmune-related illnesses like systemic sclerosis (SSc). Therefore, it is hypothesized that CDH11 could be a target for cell-specific delivery of antifibrotic therapies to fibrotic skin tissue. Here, a CDH11 peptide conjugated liposome loaded with Tofacitinib, a JAK inhibitor, was developed to understand the potential of targeted therapies to treat skin fibrosis. The …

Alteration Of Peripheral Cytokines In Alzheimer’S Disease, Zhengshi Yang

UNLV Theses, Dissertations, Professional Papers, and Capstones

Alzheimer’s disease (AD) is a progressive neurodegenerative disease with the clinical symptoms of gradual cognitive decline and memory loss. Biologically, abnormal accumulation of Aβ (Aβ) plaque and tau tangles in the brain are the core pathological hallmarks in AD. Although inflammatory response is not specific to AD, emerging evidence suggests that the disrupted innate immune system within the central nervous system, particularly microglial activation, might act as the bridge linking Aβ aggregation to pathological phosphorylation and aggregation of tau. The inflammatory response was suggested to initially have a neuroprotective role of attempting to clear Aβ plaques, and then become neurotoxic …

Delineating Genetic Influences On Neurodegenerative Disorders And Infectious Diseases Through Advanced Computational Methods, Xiaowei Zhuang

UNLV Theses, Dissertations, Professional Papers, and Capstones

Genetics plays a critical role in understanding the molecular mechanisms underlying neurodegenerative disorders and pathogen evolution in infectious diseases. For example, identifying genetic variants associated with a disease phenotype uncovers functional pathways that could lead to potential drug targets and therapeutic interventions. In addition, tracking the genetic evolution of pathogens enables early detection and warning of infectious disease outbreaks. In both applications, given the large amount of genetic data, advanced computational methods, including longitudinal and multivariate models, could significantly boost the statistical power and capture interrelationships among traits, environmental factors and genetic influences. This dissertation focuses on four applications of …

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 …

Digital Health Intervention For Children With Adhd To Improve Mental Health Intervention, Patient Experiences, And Outcomes: A Study Protocol, Nancy Herrera, Franceli L. Cibrian, Lucas M. Silva, Jesus Armando Beltran, Sabrina E. B. Schuck, Gillian R. Hayes, Kimberley D. Lakes

Engineering Faculty Articles and Research

Background

Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent childhood psychiatric condition with profound public health, personal, and family consequences. ADHD requires comprehensive treatment; however, lack of communication and integration across multiple points of care is a substantial barrier to progress. Given the chronic and pervasive challenges associated with ADHD, innovative approaches are crucial. We developed the digital health intervention (DHI)—CoolTaCo [Cool Technology Assisting Co-regulation] to address these critical barriers. CoolTaCo uses Patient-Centered Digital Healthcare Technologies (PC-DHT) to promote co-regulation (child/parent), capture patient data, support efficient healthcare delivery, enhance patient engagement, and facilitate shared decision-making, thereby improving access to …

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 …

Sex Differences In Active Avoidance And Neural Circuit Mechanisms In Contextual Fear Generalization, Carly Vincent

Theses and Dissertations

The current studies were aimed to investigate two behavioral hallmarks of anxiety and stress-related disorders, avoidance responses and the over-generalization of fear. In the first set of studies, active avoidance and extinction learning, that parallels exposure therapy in preclinical rodent models, were used. It is known that stress can influence aversive learning and extinction training, which can result in poor extinction retention. However, it is not well understood how the stress response is facilitating extinction resistance in active avoidance learning across sexes. Therefore, the first set of studies aimed to investigate the role of biological sex and glucocorticoid receptor (GR) …

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. …