Biomedical Commons^™

Compact Hardware Implementation Of A Sha-3 Core For Wireless Body Sensor Networks, Yi Yang, Debiao He, Neeraj Kumar, Sherali Zeadally

Information Science Faculty Publications

One of the most important Internet of Things applications is the wireless body sensor network (WBSN), which can provide universal health care, disease prevention, and control. Due to large deployments of small scale smart sensors in WBSNs, security, and privacy guarantees (e.g., security and safety-critical data, sensitive private information) are becoming a challenging issue because these sensor nodes communicate using an open channel, i.e., Internet. We implement data integrity (to resist against malicious tampering) using the secure hash algorithm 3 (SHA-3) when smart sensors in WBSNs communicate with each other using the Internet. Due to the limited resources (i.e., storage, …

Short-Term Tracking Of Orientation With Inertial Sensors, Golriz Sedaghat

Dissertations and Theses

In the past several years, IMU's have been widely used to measure the orientation of a moving body over a continuous period of time. Although, inertial navigation is a common approach for estimating the orientation, it greatly suffers from the accumulation of error in the orientation estimation. Most of the current common practices apply zero velocity update as a calibration method to address this problem and improve the estimation accuracy. However, this approach requires the sensors to be stationary frequently.

This thesis introduces a novel method of calibration for estimating the elevation and bank angles of the orientation over a …

Developmental Steps For A Functional Three-Dimensional Cell Culture System For The Study Of Asymmetrical Division Of Neural Stem Cells, Martina Zamponi

Biomedical Engineering Theses & Dissertations

Stem cells are a cell type present during and following development, which possess self- renewal properties, as well as the ability to differentiate into specific cells. Asymmetrical division is the cellular process that allows stem cells to produce one differentiated and one un-differentiated daughter cell during the same mitotic event. Insights in the molecular mechanisms of such process are minimal, due to the absence of effective methods for its targeted study. Currently, traditional methods of investigation include monolayer cell culture and animal models. The first poses structural limitations to the accurate representation of human tissue and cell structures, while animal …

Wearable Assistive Technologies For Autism: Opportunities And Challenges, Emma Mansouri Benssassi, Juan-Carlos Gomez, Louanne E. Boyd, Gillian R. Hayes, Juan Ye

Engineering Faculty Articles and Research

Autism is a lifelong developmental condition that affects how people perceive the world and interact with others. Challenges with typical social engagement, common in the autism experience, can have a significant negative impact on the quality of life of individuals and families living with autism. Recent advances in sensing, intelligent, and interactive technologies can enable new forms of assistive and augmentative technologies to support social interactions. However, researchers have not yet demonstrated effectiveness of these technologies in long-term real-world use. This article presents an overview of the social and sensory challenges of autism, which offer great opportunities and challenges for …

New Algorithms For Compressed Sensing Of Mri: Wtwts, Dwts, Wdwts, Srivarna Settisara Janney

Master of Science in Computer Science Theses

Magnetic resonance imaging (MRI) is one of the most accurate imaging techniques that can be used to detect several diseases, where other imaging methodologies fail. MRI data takes a longer time to capture. This is a pain taking process for the patients to remain still while the data is being captured. This is also hard for the doctor as well because if the images are not captured correctly then it will lead to wrong diagnoses of illness that might put the patients lives in danger. Since long scanning time is one of most serious drawback of the MRI modality, reducing …

Adaptation Of Vt-Dbr Lasers For Lidar, Luke Horowitz

Master's Theses

Vernier Tuned Distributed Bragg Reflector (VT-DBR) lasers have had great success in the field of Swept-Source Optical Coherence Tomography (SS-OCT) due to their continuous and nearly 40 nm wavelength tuning range in a single longitudinal mode. Fast sweeps allow for real time imaging with micrometer resolution at a distance of a few centimeters. While this laser has proven quite useful as a medical imaging tool via OCT, it has yet to similarly prove itself for general light detection and ranging (LIDAR) applications due to range limitations that arise from a finite laser coherence length. The goal of this thesis is …

Mechanism Of Virus Inactivation By Cold Atmospheric-Pressure Plasma And Plasma-Activated Water, Li Guo, Ruobing Xu, Lu Gou, Zhichao Liu, Yiming Zhao, Dingxin Liu, Lei Zhang, Hailan Chen, Michael G. Kong

Bioelectrics Publications

ABSTRACT Viruses cause serious pathogenic contamination that severely affects the environment and human health. Cold atmospheric-pressure plasma efficiently inactivates pathogenic bacteria; however, the mechanism of virus inactivation by plasma is not fully understood. In this study, surface plasma in argon mixed with 1% air and plasma-activated water was used to treat water containing bacteriophages. Both agents efficiently inactivated bacteriophages T4, ϕ174, and MS2 in a time-dependent manner. Prolonged storage had marginal effects on the antiviral activity of plasma-activated water. DNA and protein analysis revealed that the reactive species generated by plasma damaged both nucleic acids and proteins, consistent with the …

Extended-Use Ecg Monitor, Daniel Aaron Soski

Master's Theses

In this thesis, a prototype ECG monitor was developed that is integrated into an elastic shirt and takes a 3-lead ECG for over 5 days. The high-quality measurements can be used to identify markers indicative of various detrimental heart conditions. Measurements recorded by the device are encrypted and stored onto a micro-SD card. Current Holter monitors are expensive and have functional lives less than 48 hours; however, extended duration monitoring has been proven more useful in diagnosis. The device designed demonstrates that ECG measurements can be taken over longer durations without sacrificing quality, comfort, or device cost.

Subspace Averaging Of Auditory Evoked Potentials, Xiaoliang Wang

Electrical Engineering Theses and Dissertations

The auditory evoked potential (AEP) is an electric potential generated in the brain in response to auditory stimuli. It has clinical importance in the detection of newborn infant hearing loss. The signal to noise ratio (SNR) of the AEP is low, so signal averaging is typically employed to estimate it. Often, thousands of trials must be averaged before a sufficiently high SNR estimate is obtained.

In this research, we have developed a new AEP averaging method called subspace averaging. The subspace averaging method projects onto the signal subspace: the span of the principal eigenvectors of the signal correlation matrix. The …

Computational Theories For Human Stereo Vision, Han Gao

Electrical Engineering Theses and Dissertations

Binocular stereopsis refers to the ability to perceive depth, which has always been a central problem in perception since the time of da Vinci. The foremost theoretical difficulty that arises when attempting to understand how the visual system computes disparity is known as the correspondence or matching problem. Decades of research upon macaque primary visual cortex has shown that in each layer of the primary visual cortex (V1) long-range horizontal connections among striate cortex cells exist which integrate information from different parts of the visual field. Inspired by long-range horizontal connections in V1 and the Jeffress model, a time-delay neural …

Optimization Of Gpu-Accelerated Iterative Ct Reconstruction Algorithm For Clinical Use, Tao Ge

McKelvey School of Engineering Graduate Student Theses & Dissertations

In order to transition the GPU-accelerated CT reconstruction algorithm to a more clinical environment, a graphical user interface is implemented. Some optimization methods on the implementation are presented. We describe the alternating minimization (AM) algorithm as the updating algorithm, and the branchless distance-driven method for the system forward operator. We introduce a version of the Feldkamp-Davis-Kress algorithm to generate the initial image for our alternating minimization algorithm and compare it to a choice of a constant initial image. For the sake of better rate of convergence, we introduce the ordered-subsets method, find the optimal number of ordered subsets, and discuss …

Design & Delivery Of Automated Winston-Lutz Test For Isocentric & Off-Axis Delivery Stability Utilizing Truebeam Developer Mode & Electronic Portal Imaging Device, Mahmoud Mohammad Yaqoub

UNLV Theses, Dissertations, Professional Papers, and Capstones

The uncertainties in treatment delivery cannot be ignored in radiation therapy. Thus, the quality assurance QA tests are very important task of the medical physicist in clinical practice. Assuring the coincidence between the mechanical isocenter of the Linear Accelerator (LINAC) and its radiation beams isocenter is one of the most important qualities need to be tested, and the Winston Lust (WL) test is the

most popular technique to perform this task, especially for the treatment modalities which need high precision in beam delivery such as the stereotactic radiosurgery/stereotactic body radiotherapy (SRS/SBRT). The linear accelerator-based SRS/SBRT is a well-established method in …

Evaluation Of Terahertz Imaging For Breast Cancer Detection Using Image Morphing, Tanny Andrea Chavez Esparza

Graduate Theses and Dissertations

This thesis proposes the use of a mesh morphing algorithm for the quantitative evaluation of terahertz (THz) images. This work differs from traditional evaluation methods based on qualitative evaluation because it provides a fair and quantitative measurement of the THz imaging system's performance. The objective of the algorithm is to match the alignment, shape, and resolution of the THz and reference pathology images. Therefore, the proposed morphing method provides a pathology reference for a pixel-by-pixel evaluation of the region classification in the THz image. To achieve this, the morphing algorithm aligns the images using the Pearson's correlation coefficient and reshapes …

Segmentation, Tracking, And Kinematics Of Lung Parenchyma And Lung Tumors From 4d Ct With Application To Radiation Treatment Planning., Jungwon Cha

Electronic Theses and Dissertations

This thesis is concerned with development of techniques for efficient computerized analysis of 4-D CT data. The goal is to have a highly automated approach to segmentation of the lung boundary and lung nodules inside the lung. The determination of exact lung tumor location over space and time by image segmentation is an essential step to track thoracic malignancies. Accurate image segmentation helps clinical experts examine the anatomy and structure and determine the disease progress. Since 4-D CT provides structural and anatomical information during tidal breathing, we use the same data to also measure mechanical properties related to deformation of …

Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard

Electronic Theses and Dissertations

Electrophysiological measurements have been used in recent history to classify instantaneous physiological configurations, e.g., hand gestures. This work investigates the feasibility of working with changes in physiological configurations over time (i.e., longitudinally) using a variety of algorithms from the machine learning domain. We demonstrate a high degree of classification accuracy for a binary classification problem derived from electromyography measurements before and after a 35-day bedrest. The problem difficulty is increased with a more dynamic experiment testing for changes in astronaut sensorimotor performance by taking electromyography and force plate measurements before, during, and after a jump from a small platform. A …

Phase Unwrapping Of 4d-Flow Mri Data With Graph Cuts., Andrew Justice

Electronic Theses and Dissertations

A common issue when measuring velocity utilizing 4D flow magnetic resonance imaging (MRI) is aliasing that occurs because of a low velocity encoding parameter (VENC). Aliasing can be avoided if the velocity encoding parameter is set above the largest velocity quantity. However, when this is done the velocity to noise ratio is lowered less detail is acquired in the image. Thusly, it is sometimes desirable to have a below the maximum velocity to acquire higher quality data.

Consequently, an efficient and robust algorithm is needed to unwrap the aliased data. This paper proposes an iterative graph cuts algorithm to perform …

Detecting Suicide Risk From Wristworn Activity Tracker Data Using Machine Learning Approaches, Pallavi Atluri

Electrical Engineering Theses

Suicide is a prevalent cause of death worldwide and depression is a primary concern of many suicidal acts. It is possible that an individual during depression never has any suicidal thoughts at all. On the other hand, some individuals in stable condition with no apparent symptoms of depression feel urges to commit suicide (suicidal ideation). Many such individuals never let anyone know what they are feeling or planning. Suicidal ideation considered an important precursor to suicidal acts.

Detecting the suicide risk in individuals with mood disorders is a major challenge. The current clinical practice to assess suicide risk in these …

Image Processing Applications In Real Life: 2d Fragmented Image And Document Reassembly And Frequency Division Multiplexed Imaging, Houman Kamran Habibkhani

LSU Doctoral Dissertations

In this era of modern technology, image processing is one the most studied disciplines of signal processing and its applications can be found in every aspect of our daily life. In this work three main applications for image processing has been studied.

In chapter 1, frequency division multiplexed imaging (FDMI), a novel idea in the field of computational photography, has been introduced. Using FDMI, multiple images are captured simultaneously in a single shot and can later be extracted from the multiplexed image. This is achieved by spatially modulating the images so that they are placed at different locations in the …

3d Bioprinting Systems For The Study Of Mammary Development And Tumorigenesis, John Reid

Electrical & Computer Engineering Theses & Dissertations

Understanding the microenvironmental factors that control cell function, differentiation, and stem cell renewal represent the forefront of developmental and cancer biology. To accurately recreate and model these dynamic interactions in vitro requires both precision-controlled deposition of multiple cell types and well-defined three-dimensional (3D) extracellular matrix (ECM). To achieve this goal, we hypothesized that accessible bioprinting technology would eliminate the experimental inconsistency and random cell-organoid formation associated with manual cell-matrix embedding techniques commonly used for 3D, in vitro cell cultures. The first objective of this study was to adapt a commercially-available, 3D printer into a 3D bioprinter. Goal-based computer simulations were …

Deep Gaze Velocity Analysis During Mammographic Reading For Biometric Identification Of Radiologists, Hong-Jun Yoon, Folami Alamudun, Kathy Hudson, Garnetta Morin-Ducote, Georgia Tourassi

Journal of Human Performance in Extreme Environments

Several studies have confirmed that the gaze velocity of the human eye can be utilized as a behavioral biometric or personalized biomarker. In this study, we leverage the local feature representation capacity of convolutional neural networks (CNNs) for eye gaze velocity analysis as the basis for biometric identification of radiologists performing breast cancer screening. Using gaze data collected from 10 radiologists reading 100 mammograms of various diagnoses, we compared the performance of a CNN-based classification algorithm with two deep learning classifiers, deep neural network and deep belief network, and a previously presented hidden Markov model classifier. The study showed that …