Other Biomedical Engineering and Bioengineering 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 …

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. …

A Deep Learning Approach For Semantic Segmentation And Its Application On Ctc., Samir Farag Harb

Electronic Theses and Dissertations

This dissertation explores the modeling and analysis of medical images, focusing on the intricate task of colon segmentation and subsequent 3D reconstruction, which are critical steps in Computed Tomography Colonography (CTC) systems. The primary objective of this research is to develop precise segmentation approaches to enhance the accuracy of colon identification and reconstruction from abdominal CT scans. Three distinct segmentation approaches are proposed and evaluated: a Markov Random Field (MRF)-based approach, a convolutional neural network (CNN)-based deep learning (DL) approach, and a sequential episodic training with dual contrastive learning Approach (G-SET-DCL) that has a flavor of few-shot learning (FSL). To …

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 …

Conversational Voice User Interfaces Supporting Individuals With Down Syndrome: A Literature Review, Franceli L. Cibrian, Concepción Valdez, Lauren Min, Vivian Genaro Motti

Engineering Faculty Articles and Research

Conversational Voice User Interfaces (CVUIs) are widely used in commercial applications such as personal assistants. CVUIs are beneficial for most users as they enable interaction through speech and natural language. However, recent studies indicate that underrepresented user groups, such as individuals with speech impairments and specifically those with Down syndrome, face challenges in using voice commands to control CVUIs. The anatomical and physiological differences affecting the voice, speech, fluency, and prosody of users with Down syndrome hinder their experience with CVUIs. This article presents the results of 43 papers related to the use of voice user interfaces supporting individuals with …

Movian: Advancing Human Motion Analysis With 3d Visualization And Annotation, Trudi Di Qi, Isaac Browen, David Zhang, Hector M. Camarillo-Abad, Franceli L. Cibrian

Engineering Faculty Articles and Research

Human motion analysis, including data visualization and annotation, is crucial for understanding human behavior and intentions during various activities, aiding in the development of innovative tools that support independent living. Current wearable sensing technology provides rich 3D spatial movement data but generates multimodal complex datasets that require specialized skills for effective analysis. Despite the need, limited research exists on tools for effective visualization and easy annotation of such complex motion data. MoViAn (Motion Data Visualization and Annotation) is an innovative 3D data analysis system offering enriched visual representations of 3D human motion data (e.g., gaze, hand movements), along with an …

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 …

Hypoxic Incubator: Improving Robustness/Reliability And Demonstrating Physiological Efficacy, Damon Dennis Tan

Master's Theses

The Microphysiological Systems Laboratory aims to develop colorectal cancer tumor models under a hypoxic environment to assess model response to pharmaceutical compounds in vitro. To perform relevant studies, researchers have attempted to use different hypoxic inducing strategies such as a nitrogen pod and hypoxic incubator to recreate in vivo physiological responses to hypoxia. However, studies would be interrupted due to incubator functionality failure. To ensure successful and physiologically relevant studies, I improved and verified the robustness and reliability of a hypoxic incubator previously designed and manufactured in the lab. Through the testing and iterating design processes, I engineered and implemented …

Creative Insights Into Motion: Enhancing Human Activity Understanding With 3d Data Visualization And Annotation, Isaac Browen, Hector M. Camarillo-Abad, Franceli L. Cibrian, Trudi Di Qi

Engineering Faculty Articles and Research

This paper presents a novel 3D system for human motion analysis - Motion Data Visualization and Annotation (MoViAn). Designed to provide a comprehensive visual representation of 3D human motion data, MoViAn incorporates detailed visualization of gaze direction, hand movements, and object interactions, alongside an interactive interface for efficient data annotation. A user study involving eight participants indicates that MoViAn enables users to thoroughly explore and annotate human motion data, with System Usability Scale (SUS) results demonstrating a satisfactory usability level. The contribution of this paper lies in the development of an interactive and usable data analytics tool aimed at deepening …

Shape Memory Alloy Capsule Micropump For Drug Delivery Applications, Youssef Mohamed Kotb

Theses and Dissertations

Implantable drug delivery devices have many benefits over traditional drug administration techniques and have attracted a lot of attention in recent years. By delivering the medication directly to the tissue, they enable the use of larger localized concentrations, enhancing the efficacy of the treatment. Passive-release drug delivery systems, one of the various ways to provide medication, are great inventions. However, they cannot dispense the medication on demand since they are nonprogrammable. Therefore, active actuators are more advantageous in delivery applications. Smart material actuators, however, have greatly increased in popularity for manufacturing wearable and implantable micropumps due to their high energy …

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 …

Controlled Radiation Capsule For Precision And Rapid Cancer Treatment, Hoseon Lee, Zsolt Kollar, Bailey R. White, Junia Nguyen, David Roque, Sowjanya Palagani

Symposium of Student Scholars

This research aims to transform cancer treatment through the optimization of brachytherapy, with a focus on reducing treatment duration, setup complexities, and financial burdens, all while emphasizing patient safety. Patients living at a distance from radiation clinics, particularly those undergoing extended Low Dose Radiation brachytherapy, often struggle with the formidable financial challenges associated with securing nearby accommodations. In response to these issues, the research introduces a radiation capsule designed to condense the conventional six-month treatment period to approximately just one week, thereby significantly reducing the duration of required accommodations. This capsule is especially relevant considering the construction cost of $40 …

Hierarchical Based Classifcation Method Based On Fusion Ofgaussian Map Descriptors Foralzheimer Diagnosis Using T1‑Weighted Magnetic Resonance Imaging, Nourhan Zayed, Shereen E. Morsy, Inas A. Yassine

Mechanical Engineering

Alzheimer’s disease (AD) is considered one of the most spouting elderly diseases. In 2015, AD is reported the US’s sixth cause of death. Substantially, non-invasive imaging is widely employed to provide biomarkers supporting AD screening, diagnosis, and progression. In this study, Gaussian descriptors-based features are proposed to be efcient new biomarkers using Magnetic Resonance Imaging (MRI) T1-weighted images to diferentiate between Alzheimer’s disease (AD), Mild Cognitive Impairment (MCI), and Normal controls (NC). Several Gaussian map-based features are extracted such as Gaussian shape operator, Gaussian curvature, and mean curvature. The aforementioned features are then introduced to the Support Vector Machine (SVM). …

Motion-Resistant Pulse Oximetry, Ludvik Alkhoury

Dissertations

The measurement of vital signs ? such as peripheral capillary oxygen saturation (SpO₂) and heart rate (HR) levels ? by a pulse oximeter is studied. The pulse oximeter is a non-invasive device that measures photoplethysmography (PPG) signals and extracts vital signs from them. However, the quality of the PPG signal measured by oximetry sensors is known to deteriorate in the presence of substantial human and sensor movements contributing to the measurement noise. Methods to suppress such noise from PPG signals measured by an oximeter and to calculate the associated vital signs with high accuracy even when the wearer …

Counterventions: A Reparative Reflection On Interventionist Hci, Rua Mae Williams, Louanne E. Boyd, Juan E. Gilbert

Engineering Faculty Articles and Research

Research in HCI applied to clinical interventions relies on normative assumptions about which bodies and minds are healthy, valuable, and desirable. To disrupt this normalizing drive in HCI, we define a “counterventional approach” to intervention technology design informed by critical scholarship and community perspectives. This approach is meant to unsettle normative assumptions of intervention as urgent, necessary, and curative. We begin with a historical overview of intervention in HCI and its critics. Then, through reparative readings of past HCI projects in autism intervention, we illustrate the emergent principles of a counterventional approach and how it may manifest research outcomes that …

Split And Join: An Efficient Approach For Simulating Stapled Intestinal Anastomosis In Virtual Reality, Di Qi, Suvranu De

Engineering Faculty Articles and Research

Colorectal cancer is a life-threatening disease. It is the second leading cause of cancer-related deaths in the United States. Stapled anastomosis is a rapid treatment for colorectal cancer and other intestinal diseases and has become an integral part of routine surgical practice. However, to the best of our knowledge, there is no existing work simulating intestinal anastomosis that often involves sophisticated soft tissue manipulations such as cutting and stitching. In this paper, for the first time, we propose a novel split and join approach to simulate a side-to-side stapled intestinal anastomosis in virtual reality. We mimic the intestine model using …

Analyzing Physiological Signals During The Menstrual Cycle: Introducing An Application Of Circular Statistics, Krystal D. Sides

UNF Graduate Theses and Dissertations

Physiological signals are used in engineering and the sciences to determine the state of functionality of certain physiological systems such as the human endometrium. Many women use the basal body temperature method to track ovulation, or their fertile window. However, temperature tracking alone is subject to environmental factors. Non-invasive wearable devices can be tools in recording cycle-related physiological features relevant to women’s health research. This research uses the Empatica E4 wristband to track changes in the physiological features during sleep across the menstrual cycle of ovulating and non-ovulating females. Due to the cyclic nature of menstrual cycles, analytic solutions to …

Material Characterization And Comparison Of Sol-Gel Deposited And Rf Magnetron Deposited Lead Zirconate Titanate Thin Films, Katherine Lynne Miles

Mechanical Engineering ETDs

Lead zirconate titanate (PZT) has been a material of interest for sensor, actuator, and transducer applications in microelectromechanical systems (MEMS). This is due to their favorable piezoelectric, pyroelectric and ferroelectric properties. While various methods are available to deposit PZT thin films, radio frequency (RF) magnetron sputtering was selected to provide high quality PZT films with the added capability of batch processing. These sputter deposited PZT films were characterized to determine their internal film stress, Young’s modulus, composition, and structure. After characterization, the sputtered PZT samples were poled using corona poling and direct poling methods. As a means of comparison, commercially …

Classifying Electrocardiogram With Machine Learning Techniques, Hillal Jarrar

Master's Theses

Classifying the electrocardiogram is of clinical importance because classification can be used to diagnose patients with cardiac arrhythmias. Many industries utilize machine learning techniques that consist of feature extraction methods followed by Naive- Bayesian classification in order to detect faults within machinery. Machine learning techniques that analyze vibrational machine data in a mechanical application may be used to analyze electrical data in a physiological application. Three of the most common feature extraction methods used to prepare machine vibration data for Naive-Bayesian classification are the Fourier transform, the Hilbert transform, and the Wavelet Packet transform. Each machine learning technique consists of …

Pneumonia Radiograph Diagnosis Utilizing Deep Learning Network, Wesley O'Quinn

Honors College Theses

Pneumonia is a life-threatening respiratory disease caused by bacterial infection. The goal of this study is to develop an algorithm using Convolutional Neural Networks (CNNs) to detect visual signals for pneumonia in medical images and make a diagnosis. Although Pneumonia is prevalent, detection and diagnosis are challenging. The deep learning network AlexNet was utilized through transfer learning. A dataset consisting of 11,318 images was used for training, and a preliminary diagnosis accuracy of 72% was achieved.

Development Of Light Actuated Chemical Delivery Platform On A 2-D Array Of Micropore Structure, Hojjat Rostami Azmand, Hojjat Rostami Azmand

Dissertations and Theses

Localized chemical delivery plays an essential role in the fundamental information transfers within biological systems. Thus, the ability to mimic the natural chemical signal modulation would provide significant contributions to understand the functional signaling pathway of biological cells and develop new prosthetic devices for neurological disorders. In this paper, we demonstrate a light-controlled hydrogel platform that can be used for localized chemical delivery in a high spatial resolution. By utilizing the photothermal behavior of graphene-hydrogel composites confined within micron-sized fluidic channels, patterned light illumination creates the parallel and independent actuation of chemical release in a group of fluidic ports. The …

Admittance Method For Estimating Local Field Potentials Generated In A Multi-Scale Neuron Model Of The Hippocampus, Clayton S. Bingham, Javad Paknahad, Christopher Bc Girard, Kyle Loizos, Jean-Marie C. Bouteiller, Dong Song, Gianluca Lazzi, Theodore W. Berger

Engineering Faculty Articles and Research

Significant progress has been made toward model-based prediction of neral tissue activation in response to extracellular electrical stimulation, but challenges remain in the accurate and efficient estimation of distributed local field potentials (LFP). Analytical methods of estimating electric fields are a first-order approximation that may be suitable for model validation, but they are computationally expensive and cannot accurately capture boundary conditions in heterogeneous tissue. While there are many appropriate numerical methods of solving electric fields in neural tissue models, there isn't an established standard for mesh geometry nor a well-known rule for handling any mismatch in spatial resolution. Moreover, the …

Reading Robot, Gillian Watts, Andrew Myers, Sabrinna Tan, Taylor Klein, Omeed Djassemi

General Engineering

Presently, there is an insufficient availability of human experts to assist students in reading competency and comprehension. Our team’s goal was to create an improved socially assistive robot for use by therapists, teachers, and parents to help children and adults develop reading skills while they do not have access to specialists. HAPI is a socially assistive robot that we created with the goal of helping students practice their reading comprehension skills. HAPI enables a student to improve their reading skills without an educator present, while enabling educators to review the student's performance remotely. Design constraints included: physical size, weight, duration …

Ml-Medic: A Preliminary Study Of An Interactive Visual Analysis Tool Facilitating Clinical Applications Of Machine Learning For Precision Medicine, Laura Stevens, David Kao, Jennifer Hall, Carsten Görg, Kaitlyn Abdo, Erik Linstead

Engineering Faculty Articles and Research

Accessible interactive tools that integrate machine learning methods with clinical research and reduce the programming experience required are needed to move science forward. Here, we present Machine Learning for Medical Exploration and Data-Inspired Care (ML-MEDIC), a point-and-click, interactive tool with a visual interface for facilitating machine learning and statistical analyses in clinical research. We deployed ML-MEDIC in the American Heart Association (AHA) Precision Medicine Platform to provide secure internet access and facilitate collaboration. ML-MEDIC’s efficacy for facilitating the adoption of machine learning was evaluated through two case studies in collaboration with clinical domain experts. A domain expert review was also …

A Robust Lpc Filtering Method For Time-Resolved Morphology Of Eeg Activity Analysis, Jin Xu, Mark Davis, Ruairí De Fréin

Conference Papers

This paper introduces a new time-resolved spectral analysis method based on Linear Prediction Coding (LPC) method that is particularly suited to the study of the dynamics of EEG (Electroencephalogram) activity. The spectral dynamic of EEG signals can be challenging to analyse as they contain multiple frequency components and are often heavily corrupted by noise. Furthermore, the temporal and spectral resolution that can be achieved is limited by the Heisenberg-Gabor uncertainty principle [1]. The method described here is based on a z-plane analysis of the poles of the LPC which allows us to identify and estimate the frequency of the dominant …

Blood Glucose Predictor, Jessica Patterson

Electrical Engineering

For my senior project, I perform data analysis using statistical methods to determine body metrics that correlate with blood glucose levels. Working with Dr. Tina Smilkstein, I take repeat measurements from 6 different volunteers to establish trends in bodily metric data. The data taken includes weight, body fat, pulse rate, VO2, blood glucose, blood pressure, hours slept, and quality of sleep. Using these values, I use the program MiniTab to view results.

A few examples of correlations with blood glucose found in this project are:

• Systolic blood pressure for females had a regression line of 124.0 -0.3366*Blood Pressure. This indicates …

Development Of A Sonically Powered Biodegradable Nanogenerator For Bone Regeneration, Avi S. Patel

University Scholar Projects

Background: Reconstruction of bone fractures and defects remains a big challenge in orthopedic surgery. While regenerative engineering has advanced the field greatly using a combination of biomaterial scaffolds and stem cells, one matter of difficulty is inducing osteogenesis in these cells. Recent works have shown electricity’s ability to promote osteogenesis in stem cell lines when seeded in bone scaffolds; however, typical electrical stimulators are either (a) externally housed and require overcomplex percutaneous wires be connected to the implanted scaffold or (b) implanted non-degradable devices which contain toxic batteries and require invasive removal surgeries.

Objective: Here, we establish a biodegradable, piezoelectric …

Development Of A Sonically Powered Biodegradable Nanogenerator For Bone Regeneration, Avi Patel

Honors Scholar Theses

Background: Reconstruction of bone fractures and defects remains a big challenge in orthopedic surgery. While regenerative engineering has advanced the field greatly using a combination of biomaterial scaffolds and stem cells, one matter of difficulty is inducing osteogenesis in these cells. Recent works have shown electricity’s ability to promote osteogenesis in stem cell lines when seeded in bone scaffolds; however, typical electrical stimulators are either (a) externally housed and require overcomplex percutaneous wires be connected to the implanted scaffold or (b) implanted non-degradable devices which contain toxic batteries and require invasive removal surgeries.

Objective: Here, we establish a biodegradable, piezoelectric …

Methods To Remotely Eliminate Biofilm From Medical Implants Using 2.4 Ghz Microwaves, Brett Glenn

Mechanical Engineering Undergraduate Honors Theses

Infections associated with biofilm growth are usually challenging to eradicate due to their high tolerance toward antibiotics [11, 12]. Biofilms often form on the inert surfaces of medically implanted devices [13]. No matter the sophistication, microbial infections can develop on all medical devices and tissue engineering constructs [12]. Related infections lead to 2 million cases annually in the U.S., costing the healthcare system over $5 billion in additional healthcare expenses [12].

Novel solutions to biofilm’s microbial colonization span the spectrum of engineering and science disciplines. Yet a practical solution still does not exist. The research presented here will explore a …

Development Of A Myoelectric Detection Circuit Platform For Computer Interface Applications, Nickolas Andrew Butler

Master's Theses

Personal computers and portable electronics continue to rapidly advance and integrate into our lives as tools that facilitate efficient communication and interaction with the outside world. Now with a multitude of different devices available, personal computers are accessible to a wider audience than ever before. To continue to expand and reach new users, novel user interface technologies have been developed, such as touch input and gyroscopic motion, in which enhanced control fidelity can be achieved. For users with limited-to-no use of their hands, or for those who seek additional means to intuitively use and command a computer, novel sensory systems …