Electrical and Computer Engineering Commons^™

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 …

Federated And Explainable Spiking Neural Networks For Fair And Privacy-Preserving Nail Disease Diagnostics, Ch Pavani Reddy, Krishnanaik Vankdoth

Mansoura Engineering Journal

Automated nail disease diagnostics provide a non-invasive pathway for identifying underlying systemic health conditions; however, conventional centralized deep learning approaches often raise concerns related to privacy, fairness, and interpretability. Although the original NeuroNail-SNN framework demonstrated an energy-efficient and edge-ready diagnostic solution, its broader clinical adoption remained limited by unresolved trust, transparency, and ethical considerations. In this study, we propose the Federated and Explainable NeuroNail-SNN, which extends the original spiking neural architecture by integrating federated learning (FL), explainable artificial intelligence (XAI), fairness evaluation, and uncertainty quantification within a unified framework. Federated learning enables decentralized model training across hospitals and mobile clinics …

Comprehensive Mechatronic Design Methodology For 6-Dof Stationary Lower Limb Rehabilitation Exoskeleton Robot With Safety-Integrated Control Architecture, Javlonbek Rakhmatillaev Mr., Nodirbek Kimsanboyev Mr., Umidjon Takabaev Mr., Zafar Juraev3 Dr.

Chemical Technology, Control and Management

This paper presents the mechatronic design of a proposed six-degree-of-freedom (6-DOF) stationary lower limb rehabilitation exoskeleton (SLLRE) robot, developed through a comprehensive mechatronic design methodology that includes mechanical design, actuator and sensor selection, and the development of a control structure based on a safety-oriented control approach. The proposed 6-DOF SLLRE mechanical design introduces a comprehensive mechanical structure comprising bilateral hip, knee, and ankle joints, degrees of freedom, joint ranges of motion, human parameters for rehabilitation training, as well as the frames and structural elements of the proposed system. Furthermore, the selection of appropriate sensors, actuators, and control architecture for the …

Design And Development Of Biomimetic Hydrogel Interfaces For Enhanced Bioelectrical Signal Acquisition, Daniela Nikoloska

UNLV Theses, Dissertations, Professional Papers, and Capstones

Every second, human skin processes over one million sensory signals while maintaining properties such as electrical conductivity, mechanical adaptability, and regenerative capability that surpass all synthetic materials. Contemporary bioelectronic devices prove inadequate when contacting skin surfaces due to poor adhesion and electrical contact issues that prevent effective sensing. Despite advancements in wearable and bioelectronic technologies, current devices face major drawbacks when interfacing with human skin, particularly in maintaining firm adhesion, conformability, and low-noise electrical signal acquisition.

This research focuses on the development of a biomimetic hydrogel-based interface for bioelectronic sensing. Specifically, a hybrid hydrogel system composed of polydopamine (PDA)- doped …

Exploring Interactive Robotic Music Therapy Systems For Rehabilitation: A Survey Paper, Hector A. Salinas Gordillo

Discovery Undergraduate Interdisciplinary Research Internship

Interactive robotic music therapy introduces an innovative opportunity, where human guided musical interaction with robotic systems can create adaptive and engaging therapeutic experiences. This survey explores the current state of research at the intersection of robotics, music, and rehabilitation, focusing on emerging technologies such as human robot interaction methods and system designs that help enable real time, interactive music therapy.

Potential patient groups include individuals undergoing motor or cognitive rehabilitation, such as those recovering from stroke, living with Parkinson’s disease, cerebral palsy, or other motor impairments, as well as individuals with developmental disorders or limited mobility.

Traditional rehabilitation exercises may …

Impulse, Fall 2025, Jill Fier, Sierra Brown, Jerome J. Lohr College Of Engineering

Impulse (Jerome J. Lohr College of Engineering Publication)

2 | Faculty News
3 | SDSU Vet Hua to Head Civil Engineering
6 | Ad Lunam — To the Moon
10 | Building A Safety Culture
11 | Department News
12 | Surface Mount Technology Kickoff
14 | Construction Management Student, Volleyball Player Building Success Piece by Piece
16 | Student Awards, Honors
18 | Student Competition Results
20 | NASA Win Opens Doors for New Product Development Order
22 | SDSU Engineering Student Tabbed as Noblereach Fellow
26 | Knabach Award Recipient from Apprentice Lineman to Company President
28 | Metzger Create Faculty Endowment for SDSU Engineering
30 …

Optimizing Beer Fermentation Through Intelligent Control, Azizbek Nodirbekovich Yusupbekov, Mirjalol Yusupov

Chemical Technology, Control and Management

This paper presents an intelligent control approach for optimizing the beer fermentation process using fuzzy logic and adaptive neuro-fuzzy inference systems. By incorporating multivariable inputs—temperature error and pH deviation—the proposed system effectively handles the nonlinear dynamics and biological variability inherent in fermentation. Simulation results demonstrate improved control accuracy, responsiveness, and robustness compared to conventional methods, making the approach suitable for integration in modern brewery automation systems.

A Pilot Study On Tissue Deformation Using An Integrated Sensor–Actuator Blood Collection Setup In Aquaculture (Salmo Salar), Ishrak Siddiquee, Md Ebne Al Ashad, Ahmed Hasnain Jalal

Electrical and Computer Engineering Faculty Publications

This pilot study presents a sensor–actuator setup designed to evaluate tissue deformation in Atlantic Salmon (Salmo salar) during needle insertion. The system integrates three types of low-cost, commercially available force sensors to capture force profiles and identify biomechanical events associated with tissue layer transitions. Controlled insertions were performed on a deceased specimen, and the resulting force data were analyzed to quantify insertion dynamics and estimate tissue deformation. A simulation model based on the recorded force values was developed to calculate stress distribution and deformation, which ranged from 0.001 µm to 8.4 µm and from 0.3 N/m2 to 4.9 N/m2, respectively. …

Single-Molecule Orientation And Localization Microscopy, Sophie Brasselet, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Single-molecule localization microscopy (SMLM) offers enhanced spatial resolution in optical microscopy, providing detailed insights into the spatial organization of proteins in cells at the nanoscale. Over the past decade, SMLM has progressively incorporated the capability to retrieve the orientations of single molecules using their polarized dipolar emission pattern. Here we explore recent advancements in single-molecule orientation and localization microscopy (SMOLM), which yields super-resolved images of molecular three-dimensional (3D) orientations, wobble and 3D positions. This advancement opens possibilities to explore the nanoscale organization and conformation of biological molecules as well as to monitor and design local 3D optical fields in nanophotonics. …

Predicting The Response Of Tendon-Driven Prosthetic Finger With Hyperelastic Joints, Lucas Gallup, Mohamed Trabia, Brendan O'Toole

Mechanical Engineering Faculty Research

Properly designed prosthetics hands can enhance the quality of life for those suffering from limb loss. Recently, 3D-printed prosthetic hands are becoming common. In these prostheses, fingers flex through the tendons that are activated by motion of the wrist. To provide spring action, thermoplastic polyurethane (TPU) hyperelastic joints are used to connect digits to each other as well as to the wrist. While these designs are common, no model for the relationship between tendon tension and joint flexion is available. This work has developed a quasi-static virtual work-based model to predict the relationship between tendon forces and the flexion of …

Sar Analog-To-Digital Converters For Point-Of-Care Biosensors: A Comparison, Eithar Alammari, Joud Alamro, Sara Alashwali, Ghadah S. Alyami, Aziza I. Hussein

Effat Undergraduate Research Journal

The SAR ADC, recognized for its low power consumption, moderate resolution, and satisfactory processing speed, stands as an ideal choice for ultra-low power biomedical applications. Recent efforts have been concentrated on enhancing the power efficiency of the SAR ADC sub-components through intricate refinements and innovative techniques. These efforts aim to minimize energy consumption without compromising the ADC's performance. Therefore, this paper aims to thoroughly examine various implementation approaches for the main components of the SAR ADC, highlighting their individual strengths, weaknesses, and limitations within wireless biomedical applications.

Functional Biopolymers Applied To Sustainable Technologies In The Environment And Healthcare, Fengjie He

UNLV Theses, Dissertations, Professional Papers, and Capstones

Biodegradable polymeric materials (biopolymers) are naturally derived materials known for their excellent biocompatibility, biodegradability, sustainability, and versatile chemical functionality. They have attracted increasing attention in various applications as alternative to synthetic materials ranging from food packaging to tissue engineering. Meanwhile, with intrinsic advantages, biopolymers have also emerged as promising materials in addressing contemporary challenges in both biomedical and environmental fields. Motivated by the significant potential of biopolymers and the growing need for sustainable materials, my research focuses on the design and engineering of biodegradable polymers with novel modification methods and application directions. In this work, two representative biopolymers are selected: …

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 …

Ac Electric Fields Manipulate And Concentrate Dna Molecules On Electrodes, Akila Wijesinghe, Dharmakeerthi Nawarathna

Graduate Student Government Association Research Conference

Point-of-care (POC) electric field-based biosensors have emerged as a promising tool to detect early cancer biomarkers such as circulating tumor DNA (ctDNA), microRNA (miRNA), and proteins. To be effective in screening in clinical settings, these biosensors must be simple and easy to use. In this study, we have studied the manipulation of short DNA molecules suspended in a sessile drop to achieve this goal. Alternative current (AC) electric fields were used to polarize DNA molecules and produce dielectrophoretic (DEP) force on DNA molecules. DEP force is used to manipulate polarized DNA molecules towards the higher electric field gradients (toward the …

A Smart System For Detecting Anatomic And Histological Symptoms Of Diseased Agricultural Plants, Rustam Baratov, Himola Sunnatillayeva, Alimardon Mamatovich Mustafoqulov

Chemical Technology, Control and Management

This study describes a novel agricultural plant disease detecting smart system, capable of handling measured plant body parameters and images received by high resolution camera at the same time. The proposed plant disease detection method is based on evaluation of the signals received by measured and controlled plant body physical parameters like resistance, temperature and capacitance of the plant stem and image processing. An analogue plant model based on an electrical circuit with distributed parameters was developed. In addition, in the article the block diagram of the smart system for the early detection of plant diseases, the circuit diagram, its …

Advancements In Refreshable Braille Display Technology: A Comprehensive Survey, Maryam Etezad, Rajeev Joshi, Franceli L. Cibrian

Engineering Faculty Articles and Research

This paper provides a comprehensive mapping literature review of the advancements in refreshable Braille display (RBD) technology, which employs dynamically movable pins or dots to render Braille characters for individuals with blindness and visual impairment. This literature review, which includes 96 papers, aims to summarize the current evidence on six distinct types of RBDs: piezoelectric, electromagnetic, electroactive polymer (EAP), pneumatic, shape memory alloy (SMA), and microfluidic technologies. For each type, we discuss the underlying mechanisms, alongside the current trends and research opportunities. This comparative analysis aims to inform the selection of appropriate RBD technology based on specific user needs and …

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 …

Deep Learning In Lung Cancer Pre- And Post-Radiation Therapy: Diagnosis Of Malignancy And Radiation-Induced Lung Injury From 3d X-Ray Ct., Benjamin Peter Veasey

Electronic Theses and Dissertations

Lung cancer remains the leading cause of cancer-related mortality worldwide, with early detection and accurate diagnosis being critical for improving patient outcomes. Additionally, the progression of Radiation-Induced Lung Injury (RILI) following Stereotactic Body Radiation Therapy (SBRT) for lung cancer presents a significant diagnostic challenge. This dissertation addresses these challenges by developing deep learning-based diagnostic tools for both pre-treatment lung nodule malignancy classification and post-treatment RILI identification using 3D X-ray CT imaging. The research is divided into two primary objectives. First, for lung nodule malignancy classification, we developed a biopsy-confirmed dataset, called NLSTx, to train and evaluate deep learning models while …

Development Of A Portable Electroencephalogram With Display, Seth D. Davis

Electronic Theses and Dissertations

In this experiment, the goal was to design, build, and test an Electroencephalogram (EEG) circuit that would then be paired with a touchscreen display as a portable unit for use in Schizophrenic research at East Tennessee State University at the Quillen College of Medicine. The requirements for this prototype denoted that the device had to be able to obtain a signal from two electrodes placed on the head of an individual with a third attached to the ankle as a ground, amplify and filter the signal, and display the results on a touchscreen display for recording and analyzing. The circuit …

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 …

Using Eeg Signal For Smart Health: An Overview, Addison Clark, Chelsea Bonyata, Ishfaq Ahmad, Hansheng Lei, Khalid Saifullah, Victor Ibarra

Informatics and Engineering Systems Faculty Publications

This survey paper aims to provide an overview of the current state of EEG (Electroencephalography) signal technology as it relates to people with disabilities. It will highlight the various methods and techniques employed, discussing their advantages and disadvantages. The paper will also examine the applications of EEG technology in assisting individuals with disabilities, specifically focusing on Brain-Computer Interfaces (BCIs) and assistive device control. By understanding the current state of EEG signal technology, we can identify the opportunities and challenges involved in utilizing this technology to improve the lives of people with disabilities.

Clinical Use Of Sit2stand Ai Application For Kinematic Analysis In Prosthesis Users., Samerial Brown

Posters - 2025

Biomechanical analysis is a tool to evaluate prosthetic and orthotic patient's. These tools offer the clinician capability of understanding the mechanism of injury, gait deviation or prosthesis problem. Video based analysis require expensive hardware, software, and training which sometimes costs $40-100,000.

The recent advent of artificial intelligence (AI) has opened up the possibility of acquiring high speed human motion video analysis using low-cost hardware and open-source machine learning algorithms. Still, free assessments like the Sit2Stand test is a current clinical outcome measure which assesses ability of a patient to stand and sit as fast as possible 5x. The faster the …

Development Of Laser-Induced Graphene-Based Bioanode Incorporating Thylakoid For Harvesting Energy, Amit Sarode

Biomedical Engineering Theses & Dissertations

Thylakoid-Based Biofuel Cells (TBFCs) present significant potential as renewable power sources; however, their development is impeded by challenges including delicate thylakoid membranes, limited electron transport efficiency, stability and dependence on expensive mediators. This study aimed to address these challenges by fabricating a novel photo-driven bioanode through the integration of Laser-Induced Graphene (LIG), Nb₄C₃T_x MXene, and thylakoid membranes. The fabrication process involved laser engraving to generate porous LIG electrodes, followed by MXene drop casting and thylakoid immobilization to enhance electrochemical performance and surface area. Morphological characterization supported that MXene incorporation increased active sites and surface roughness, …

Painting Rich Six-Dimensional Pictures Using Polarized Fluorescence Microscopy, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

No abstract provided.

Development And Analysis Of The Kinematic-Dynamic Model Of The Rehabilitation Exoskeleton System, Umidjon Abdumutalipovich Takabaev, Zafar Botirovich Juraev

Technical science and innovation

Designing modern rehabilitation exoskeleton systems requires a comprehensive study of human-machine interactions. In this process, creating kinematic and dynamic mathematical models of the system is extremely important. In this paper, we develop mathematical models that describe rehabilitation exoskeleton systems' kinematic and dynamic properties. Based on the Denavit-Hartenberg method we construct kinematic model of the exoskeleton system. The method gave us to determine the coordinate system for each joint. Furthermore, we also study the motion range of joints of the exoskeleton. Modeling the dynamic properties of the system performed with the second-order Lagrange equation. The exoskeleton construction consisting of knee, thigh, …

Emg-Based Intraoperative Neuromonitoring Using Advanced Machine Learning Approaches, Abdalla Nabil Elsharkawy, Nourhan Zayed

Mechanical Engineering

Intraoperative neuromonitoring (IONM) plays a critical role in minimizing nerve damage during surgeries by providing real-time feedback on neural integrity. This study evaluated models associated with deep learning and machine learning models for electromyography classification of signal during intraoperative neuromonitoring (IONM). The CNNLSTM model achieved the highest accuracy (85.2%), outperforming traditional models like KNN (53%), RF (62%), and CNN (76%). This demonstrates the degree to which the CNN-LSTM model can gain insight into temporal and spatial dependencies throughout the EMG signals, which makes it optimal for real-time classification in IONM applications. This implies that deep learning techniques can improve surgical …

Neurophisology Biosignals Of Cognitive Training Classification In Virtual Reality Environment Using Deep Learning Model, Nourhan Zayed, Mohamed Reda

Mechanical Engineering

This research investigates the potential of neurophysiological biosignals fusion, such as electroencephalogram (EEG) and Eye Tracking signals (ET), to classify cognitive states during virtual reality (VR) training, specifically for the rehabilitation of neurodegenerative diseases. By analyzing EEG data collected from participants engaged in VR-based cognitive exercises, we aim to identify patterns associated with different cognitive states and develop a robust classification system. A Convolutional Neural Network (CNN) model was developed to predict task performance utilizing neurophysiological inputs in an immersive world. This system could be used to monitor cognitive function, assess treatment efficacy, and provide real-time feedback to adapt the …

Electrochemical Detection Of Dopamine Using Screen-Printed Graphene Electrode For Cancer Diagnosis And Therapy, Pritu P. Sarkar, Nazmul Islam

Research Symposium

Background: Dopamine plays a critical role in various essential functions, including motor control, hormone regulation, cognition, learning, and the reward system. In healthy individuals, dopamine levels are extremely low, with concentrations ranging from 0 to 0.25 nM in blood and 0.3 to 3.13 µM in urine. Abnormal levels are linked to disorders like Parkinson’s, schizophrenia, Alzheimer’s, epilepsy, hypertension, and arrhythmia. Abnormal dopamine levels can indicate the presence of certain cancers. Dopamine receptors may be therapeutic targets for treating cancer, especially breast and colon cancer. Thus dopamine can increase the efficacy of anticancer drugs in breast and colon cancer. Detecting dopamine …

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 …

Advancing Prosthetic Technology: 3d-Printed Robotic Arm With Micro Linear Actuators, Vu Tran, Nathan Reed, Mahdi Yazdanpour

Posters-at-the-Capitol

The increasing demand for affordable and accessible prosthetic solutions has driven innovation in the field of robotics. In this project, we present the design and development of a 3D-printed robotic prosthetic arm aimed at addressing the challenges faced by individuals with upper limb amputations. Our prosthetic arm utilizes five micro linear actuators to achieve precise and naturalistic movement. The design of the prosthetic arm prioritizes affordability and accessibility, with a focus on leveraging 3D printing technology to reduce manufacturing costs and enable customization. The use of micro linear actuators offers advantages in terms of compactness, lightweight construction, and efficient power …