Biomedical Engineering and Bioengineering Commons^™

Susceptibility To High-Fidelity Misinformation: An Eye-Tracking Analysis, Yasasi Abeysinghe, Gavindya Jayawardena, Enkelejda Kasneci, Sampath Jayarathna

Computer Science Faculty Publications

With the rise of online misinformation and AI-generated text, understanding human perception of news truthfulness is critical. In this study, we examine visual attention and cognitive processing using eye-tracking measures as individuals read fake and real news articles sharing nearly identical structure and imagery, differing only in subtle textual changes. Using the public FakeNewsPerception dataset, we analyze advanced gaze measures, including scanpaths, AOI transitions, and luminance-corrected pupil measures, beyond basic gaze features, in relation to news truthfulness and perceived believability. Results show that, given the high fidelity of the fake news, readers exhibited comparable visual scanning patterns, attention allocation across …

Advancing Cns Tumor Management: Novel Modalities In Surgery, Radiation, And Chemotherapy, Armin David Tavakkoli

Dartmouth College Ph.D Dissertations

Most tumors affecting the brain and spine are managed through a combination of surgical resection, radiation, and chemotherapy; however, operative morbidity from invasive surgery, the narrow therapeutic window of conventional radiotherapy, and poor blood-brain barrier penetration of systemic agents are critical barriers that hinder long term tumor control. This thesis presents three complementary strategies to advance brain and spine tumor therapy. First, we investigate laser interstitial thermal therapy (LITT) in the treatment of spinal tumors with metastatic epidural spinal cord compression, replacing “separation surgery” with a minimally invasive, image-guided approach that maximizes tumor ablation while preserving neurologic function. Second, we …

Crashheart, Ellie Riekert, Kennady Skidmore, Madison Furino

Williams Honors College, Honors Research Projects

This project aims to develop an XR (extended reality) iPad training system to improve pediatric crash cart preparedness among nurses and clinical staff at Akron Children’s Hospital. In emergencies such as respiratory failure or shock, quick and accurate access to crash cart supplies is vital, yet opportunities for hands-on practice are limited. Current nurse training relies on PowerPoint instruction or costly physical simulations, reducing engagement and skill retention. Our interactive XR solution replicates the crash cart’s layout and contents, allowing users to practice identifying and retrieving critical items in a realistic environment without using physical supplies. The system will be …

Stentrx, Emma Barna, Minuthi Cooray, Bruce Newlands, Joseph A. Sabetta

Williams Honors College, Honors Research Projects

This project aims to develop a biodegradable, drug-eluting biliary stent for the treatment of biliary cancers. Current metal stents that restore bile flow bit are non-degradable, prone to migration, and unable to deliver drugs locally. The proposed stent will be biocompatible, biodegradable, and capable of controlled drug release to both maintain bile flow and treat tumors. The end goal is to produce a functional prototype that can be deployed via a minimally invasive catheter and maintain bile duct patency for at least three months. The project is expected to be involved in the NEOMED Bench-to-Bedside competition and provisionally patented.

Injectable Hydrogels For Bone Regeneration: Mechanical Reinforcement Strategies Using Nanoparticles And Nanofibers: Review Paper, Fariba Ganji, Morteza Mirzagoli, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Background and Purpose: The growing demand for bone regeneration following severe injuries highlights the importance of scaffolds in bone tissue engineering (BTE). Injectable hydrogels have emerged as promising candidates because their properties closely mimic the native extracellular matrix (ECM). However, their limited mechanical strength and structural instability restrict their practical application. Approach: This review summarizes recent strategies for reinforcing in situ-forming injectable hydrogels to improve their mechanical performance for bone regeneration. Particular emphasis is placed on nanomaterial-based strategies, including the incorporation of nanoparticles and nanofibers, and their ability to enhance the physical properties of polymeric networks. Key Results: Evidence from …

Engineering Plga Nanoparticle Size To Modulate Immune Responses After Spinal Cord Injury, Daniel J. Kolpek

University of Kentucky Doctoral Dissertations

Spinal cord injury is a severe and debilitating condition that often results in lifelong complications, including paralysis. Many of these chronic outcomes are driven by a sustained inflammatory response at the injury site, which limits tissue regeneration and functional recovery. As a result, therapeutic strategies that modulate this immune response have gained significant interest. Polymer based nanoparticle therapies have emerged as a promising approach due to their ability to interact with and influence immune cell behavior. Importantly, the physicochemical properties of nanoparticles can be precisely tuned to optimize these effects. Among these properties, size has been shown to influence key …

Standardization Of Neuromuscular Reflex Analysis—Role Of Fine-Tuned Vision-Language Model Consortium And Openai Gpt-Oss Reasoning Llm-Enabled Decision Support System, Eranga Bandara, Ross Gore, Sachin Shetty, Ravi Mukkamala, Christopher K. Rhea, Brittany S. Samulski, Amin Hass, Atmaram Yarlagadda, Shaifali Kaushik, Malith De Silva, Andriy Maznychenko, Inna Sokolowska, Kasun De Zoysa

VMASC Publications

Background/Objectives: Accurate assessment of neuromuscular reflexes, such as the Hoffmann reflex (H-reflex), plays a critical role in sports science, rehabilitation, and clinical neurology. Conventional interpretation of H-reflex electromyography (EMG) waveforms is subject to inter-rater variability and interpretive bias, limiting reliability and standardization. This study aims to develop an automated, interpretable, and robust agentic AI–driven framework for H-reflex waveform analysis. Methods: We propose a fine-tuned Vision–Language Model (VLM) consortium combined with a reasoning Large Language Model (LLM)–enabled decision support system for automated H-reflex interpretation. Multiple VLMs were fine-tuned on curated datasets of H-reflex EMG waveform images annotated with expert clinical observations, …

Evaluating The Impact Of Cognitive Distraction On Spaceflight-Relevant Task Performance Using Surface Electromyography And Motion Capture, Allyson K. Mitchell

UNF Graduate Theses and Dissertations

Cognitive distraction poses a risk to astronaut performance during complex, multitasking operations in spaceflight environments. This study examined the effects of cognitive load on neuromuscular coordination and task execution using surface electromyography (sEMG) and motion capture. Thirteen participants performed spaceflight-relevant tasks under undistracted and distracted conditions, with distraction induced through verbal questioning. EMG signals from eight upper-extremity muscles were processed using envelope filtering, peak normalization, and time normalization to enable inter-subject comparison, and group-level mean activation with standard deviation was analyzed. While overall muscle activation was similar between conditions, phase-dependent differences were observed, with undistracted trials showing higher activation during …

Integrated Optical Probes For Confocal Scanning Imaging And Adjustable Coherent-Gated Dynamic Sensing, Yonglin Huang

Graduate Studies Theses and Dissertations 2026

Optics and photonics have been one of the most important sciences and technologies that impact modern human life in a big way. For example, fiber-optics for communications and artificial intelligence. Optical probes are critical components for optical imaging and optical sensing technologies that have been actively researched and developed in the past decades. Advanced fiber-optic sensor probes with smaller size, better performance, lower noise, higher photon efficiency, rapid sensing time, and lower cost are needed in many applications, such as nanoscale material science, chemistry, and biomedical fields, etc.  In this project, new fiber-optic sensor probe technologies and integrated micro-optic devices …

Mathematical Modeling And Characterization Of A Variable Stiffness Ankle-Foot-Orthosis, David E.L. Richards

Graduate Studies Theses and Dissertations 2026

Conventional ankle–foot orthoses (AFOs) typically employ static stiffness profiles that do not replicate the dynamic quasi-stiffness of the human ankle during gait. Variable stiffness mechanisms (VSMs) offer a promising alternative solution for gait pathologies, such as foot drop and post-stroke hemiparesis; however, their implementation is limited by the lack of accurate mathematical models capable of predicting force and stiffness characteristics. The objective of this thesis is to develop and validate comprehensive mathematical models describing the kinematics and kinetics of a novel variable stiffness ankle–foot orthosis (VS-AFO). This study derives governing equations to characterize how mechanical adjustments influence the force transmission …

Evaluating The Brain-Muscle Connectivity Of Cyclic Ankle Pedaling Movement In A Clinical Setting, Matthew K. Shanosky

Graduate Studies Theses and Dissertations 2026

Clinical neurorehabilitation requires objective biomarkers to accurately detect and monitor neuromotor impairments. While traditional metrics are favored for their efficiency and minimal equipment demands, they typically rely on subjective observation and lack physiological resolution. High-resolution electrophysiological technologies, such as electroencephalography (EEG) and electromyography (EMG), offer objective insights into nervous system dynamics; however, prolonged data acquisition times have hindered their translation into frontline clinics. To bridge this translational gap, this study developed a time-efficient experimental paradigm designed for rapid clinical deployment. Healthy participants completed two initial resting baseline trials before performing an externally paced, dynamic, cyclic ankle movement task utilizing simulation …

Volumetric Fluorescence Microscopy For High-Throughput And High-Sensitivity Imaging: From Single Molecules To Tissues, Le-Mei Wang

Graduate Studies Theses and Dissertations 2026

Fluorescence microscopy is an indispensable tool in the biological sciences, enabling researchers to investigate intricate subcellular structures, particularly for volumetric studies. However, conventional optical microscopy for volumetric imaging remains fundamentally constrained by imaging speed and throughput. To bypass traditional serial z-scanning, we introduce an axially scan-free method using a phase layer cake to modulate the system's point spread function. This approach projects volumetric information onto a 2D plane in a single shot, offering high flexibility in tuning axial depth alongside simultaneous multicolor imaging with high spatial resolution and sensitivity. This dissertation divides these technical advancements into cellular and tissue imaging …

A Reconstruction Method For The Anisotropic Electrical Conductivity In A Hybrid Planar Inverse Problem, Athanasios Dimitriadis

Graduate Studies Theses and Dissertations 2026

Some single-physics medical imaging methods fail to reliably discriminate benign from malignant biological tissue. In partial response, a new class of inverse problems employ multi-physics phenomena, coupling methods of high resolution with methods of high contrast. In this thesis we are concerned with one such problem in which an anisotropic electrical conductivity is to be recovered from some internal knowledge of the current density field generated by maintaining a fixed boundary voltage. This internal data is obtained by the method of Current Density Impedance Imaging (CDII), which combines Maxwell's equations with Magnetic Resonance Imaging (MRI) measurements. The anisotropy class is …

Microgravity-Induced Alterations In Left Atrial Hemodynamics And Thrombogenic Risk: Insights From Healthy And Atrial Fibrillation Models, Grace M. Hoeppner

Dissertations, Master's Theses and Master's Reports

Background: Microgravity exposure alters cardiovascular loading, yet its impact on left atrial flow dynamics and thrombotic risk remains poorly understood. This study investigates how spaceflight-relevant microgravity-induced changes in cardiac outflow affect left atrial hemodynamics in healthy individuals and patients with atrial fibrillation.

Methods: Patient-specific left atrial models were generated for three healthy individuals and three AF patients. Computational fluid dynamics (CFD) simulations were performed using each patient’s baseline mitral outflow waveform and two modified waveforms representing short- and long-duration post-flight cardiac loading changes derived from echocardiographic observations. Hemodynamic metrics included left atrial velocity, time averaged wall shear stress, oscillatory shear …

Probing Proficiency-Related Neural Representations With Pca And Ica, Onila R. Narayana Mudalige Don

Graduate Student Theses, Dissertations, & Professional Papers

How proficiency-related information is represented in task fMRI depends not only on the data themselves, but on the representational lens used to summarize them. This thesis examines second-language (L2) proficiency as a problem of representational organization rather than as a simple classification exercise. Using task fMRI from adult language learners performing semantic animacy judgments in their native language (L1) and second language (L2), I derive shared low-dimensional network representations with principal component analysis (PCA) and independent component analysis (ICA), then evaluate those representations under matched leakage-controlled decoding pipelines.

Across analyses, the central comparison is between representational frameworks rather than between …

Wip: Arduino-Based Pbl To Foster Entrepreneurial Mindset, Nathan Q. Holland, Vukica M. Jovanovic

Engineering Technology Faculty Publications

This work-in-progress paper examines a semester-long project-based learning initiative begun in an introductory engineering course during the Fall 2025 semester. The project aims to enhance students' hands-on experience by integrating information literacy, the engineering design process (EDP), and an entrepreneurial mindset (EM) [1]. The objective is to boost student confidence in teamwork, technical problem-solving, and application of skills, preparing them for future courses in their discipline. Students in this introduction to engineering course received an Arduino Uno R3 Controller board kit and additional sensors. They were tasked to develop a device addressing engineering in the medicine challenge of their choosing. …

Modeling Healthcare Data With Logistic Quantile And Uniform-Based Mixture Polynomial Distributions, Mohan D. Pant, Aditya Chakraborty, Jovanna A. Tracz

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Continuous healthcare data often deviate from normality, which can substantially increase the risk of making invalid inferences, given that many inferential statistical procedures rely on normality assumption. To obviate this issue, we propose a new family of non-normal distributions based on a linear combination of the quantile functions of standard logistic and uniform (0, 1) distributions. This new family of non-normal distributions is studied within three different methods: L-moments, conventional moments, and percentiles. Its performance is compared among the three methods in the context of parameter estimation and data modeling. The results of Monte Carlo simulation and bootstrapping techniques indicate …

Multisystem Predictors Of Dynamic Gait Stability Across Fall Risk In Older Adults, Ashwini Kulkarni, Neda Moghim, Ross Gore, Soumya Banerjee, Christopher K. Rhea, Brittany Samulski

Rehabilitation Sciences Faculty Publications

Gait stability arises from interactions between physiological, cognitive, and psychological systems, yet these domains are often assessed in isolation. This study examined multisystem predictors of anteroposterior margin of stability during walking (MoSAP) in community-dwelling older adults. Of 340 participants, 143 were retained after data quality screening (105 females; age: 70.8 ± 7.8 years). Participants completed the Physiological Profile Assessment (PPA), cognitive testing using Montreal Cognitive Assessment (MoCA), fear-of-falling evaluations using Modified Falls Efficacy Scale (MFES) and a biomechanical gait assessment during preferred and fast speeds. Participants were stratified into four PPA-based fall-risk groups: low, mild, moderate, and high risk. MoSAP …

Radial And Carotid Arterial Pulse Signals For Assessing Cardiovascular Function At Rest And During Post-Exercise Recovery In A Heart Transplant Patient: A Case Study, Md Mahfuzur Rahman, Mamun Hasan, Jennifer F. May, John M. Herre, Leryn Reynolds, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

Aim: This study investigates the feasibility of using radial and carotid arterial pulse signals to assess cardiovascular (CV) function at rest and during post-exercise recovery in a heart transplant (HTx) patient. Method: Two micro-fabricated tactile sensors were used to simultaneously acquire arterial pulse signals at the radial artery (RA) and carotid artery (CA). Measurements were taken at rest and at multiple time points post-exercise on three subjects: an HTx patient, a percutaneous coronary intervention (PCI; coronary stent) patient and a healthy control. An SDOF-TF-based time-frequency analysis algorithm was applied to extract a comprehensive set of CV parameters, including heart rate …

Mechanical-Medical Convergence In Heart Failure: Artificial Intelligence, Finite-Element Modeling, And 3d Printing For Diagnosis And Prognosis, Quazi Noor E. Sabrina, Quazi Md Zobaer Shah, Quazi Noor E. Sohela, Md Mahabub Hasan Mousum, Md. Moyeen Uddin Chisty

Mechanical & Aerospace Engineering Faculty Publications

Heart failure remains a leading cause of global morbidity and mortality, yet routine clinical indices often miss the regional biomechanical disturbances that drive progression and shape treatment response. This State-of-the-Art review examines how finite-element (FE) modeling, additive manufacturing, and artificial intelligence (AI) are converging to improve the diagnosis, phenotyping, procedural planning, and prognostic assessment of heart failure (HF). Although these technologies have matured in structural heart disease and transcatheter intervention research, their greatest translational potential may lie in HF, where patient-specific ventricular remodeling, myocardial stress-strain heterogeneity, valve-ventricular coupling, and device-tissue interaction are incompletely captured by conventional clinical indices. We synthesize …