Biomedical Commons^™

Diy Cell Incubator, Hayden James Jeanor

Electrical Engineering

The purpose of creating a cell Incubator is for the development of cell and tissue production in laboratory settings. Large scale research projects and the medical community grow cells for various reasons, including experiments and creating tissue for patients. However, they cannot simply depend on growing cells in a petri dish that sit on a rack at room temperature. To grow heathy cells in the fastest way possible, they use cell incubators. Cell incubators create an atmosphere within the incubation bay that is designed to promote cell growth. The three main components that need to be constantly regulated, using a …

Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami

Future Computing and Informatics Journal

This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today's banking sector is fraud detection. Fraud is one of the most serious concerns in terms of monetary …

Neural Network Based Diagnosis Of Breast Cancer Using The Breakhis Dataset, Ross E. Dalke

Master's Theses

Breast cancer is the most common type of cancer in the world, and it is the second deadliest cancer for females. In the fight against breast cancer, early detection plays a large role in saving people’s lives. In this work, an image classifier is designed to diagnose breast tumors as benign or malignant. The classifier is designed with a neural network and trained on the BreakHis dataset. After creating the initial design, a variety of methods are used to try to improve the performance of the classifier. These methods include preprocessing, increasing the number of training epochs, changing network architecture, …

Closed-Loop Brain-Computer Interfaces For Memory Restoration Using Deep Brain Stimulation, David Xiaoliang Wang

Electrical Engineering Theses and Dissertations

The past two decades have witnessed the rapid growth of therapeutic brain-computer interfaces (BCI) targeting a diversity of brain dysfunctions. Among many neurosurgical procedures, deep brain stimulation (DBS) with neuromodulation technique has emerged as a fruitful treatment for neurodegenerative disorders such as epilepsy, Parkinson's disease, post-traumatic amnesia, and Alzheimer's disease, as well as neuropsychiatric disorders such as depression, obsessive-compulsive disorder, and schizophrenia. In parallel to the open-loop neuromodulation strategies for neuromotor disorders, recent investigations have demonstrated the superior performance of closed-loop neuromodulation systems for memory-relevant disorders due to the more sophisticated underlying brain circuitry during cognitive processes. Our efforts are …

The Factors Influencing The Acceptance Of Web-Based E-Learning System Among Academic Staffs Of Saudi Arabia, Ikhlas Zamzami

Future Computing and Informatics Journal

It is possible to learn more quickly and effectively with e-learning software development because it provides learners with convenient and flexible learning environments. This allows them to progress further in their careers. Reports on web-based e-learning systems for in-service education have frequently neglected to include the viewpoint of the instructor. In order to conduct quantitative research, a sample of 50 academic staff members was selected. The purpose of this study was to investigate various factors that influence the intention to use web-based e-learning, with the theoretical foundation being provided by university lecturers. According to the findings of the study, the …

Development Of Sensor, Sensory System And Signal Processing Algorithm For Intelligent Sensing Applications, Xingzhe Zhang

Dissertations

Sensors have been receiving significant attention in the last decade and the demand for sensory systems has increased in recent years due to the rapid growth in the field of artificial intelligence (AI). Sensors can improve people’s awareness by providing them with real-time information on the environment and their immediate health conditions. This dissertation presents the fulfilment of three main projects and focuses on the development of a sensor, a sensory system, and a sensor signal recognition system for AI applications by employing printed electronics, analog circuit design, and digital signal processing techniques.

In the first project, a multi-channel stethograph …

Review Of Data Mining Techniques For Detecting Churners In The Telecommunication Industry, Mahmoud Ewieda, Mohamed Ismail Roushdy, Essam Shaaban

Future Computing and Informatics Journal

The telecommunication sector has been developed rapidly and with large amounts of data obtained as a result of increasing in the number of subscribers, modern techniques, data-based applications, and services. As well as better awareness of customer requirements and excellent quality that meets their satisfaction. This satisfaction raises rivalry between firms to maintain the quality of their services and upgrade them. These data can be helpfully extracted for analysis and used for predicting churners. Researchers around the world have conducted important research to understand the uses of Data mining (DM) that can be used to predict customers' churn. This …

Comparative Study Of Nano-Rod And Nano-Sphere Based Localized Surface Plasmon Resonance Refractive Index Biosensors, Mariam M. Moussilli M. M. Moussilli, Abdul Rahman El Falou

BAU Journal - Science and Technology

Localized Surface Plasmon Resonance (LSPR) waves generated by the interaction of light with noble metal nanoparticles has been of great interest in recent years due to the high sensitivity of the extinction spectra of these nanoparticles to the medium's surrounding refractive index up to the atomic level.

In this article, we simulate the extinction spectra of noble metal sphere and rod nanoparticles in order to study the effect of the geometrical shape and size of the nanoparticle on the sensitivity and detection accuracy performance parameters of the extinction spectra. We also simulated the response of the sphere and rod nanoparticle's …

Multilayer Perceptron With Auto Encoder Enabled Deep Learning Model For Recommender Systems, Subhashini Narayan

Future Computing and Informatics Journal

In this modern world of ever-increasing one-click purchases, movie bookings, music, health- care, fashion, the need for recommendations have increased the more. Google, Netflix, Spotify, Amazon and other tech giants use recommendations to customize and tailor their search engines to suit the user’s interests. Many of the existing systems are based on older algorithms which although have decent accuracies, require large training and testing datasets and with the emergence of deep learning, the accuracy of algorithms has further improved, and error rates have reduced due to the use of multiple layers. The need for large datasets has declined as well. …

Error Prevention In Sensors And Sensor Systems, Pedro J. Chacon Dominguez

LSU Doctoral Dissertations

Achievements in all fields of engineering and fabrication methods have led towards optimization and integration of multiple sensing devices into a concise system. These advances have caused significant innovation in various commercial, industrial, and research efforts. Integrations of subsystems have important applications for sensor systems in particular. The need for reporting and real time awareness of a device’s condition and surroundings have led to sensor systems being implemented in a wide variety of fields. From environmental sensors for agriculture, to object characterization and biomedical sensing, the application for sensor systems has impacted all modern facets of innovation. With these innovations, …

The Linear And Non-Linear Relationships Between Peripheral Venous Pressure, Arterial Circulation, And Patient Factors, Lauren Crimmins

Biomedical Engineering Undergraduate Honors Theses

Peripheral venous pressure (PVP) can be used to measure blood volume status with a minimally invasive procedure. The pediatric cohort undergoing surgery for pyloric stenosis was studied to determine how arterial circulation and patient factors linearly impact PVP. The relationship between PVP and these confounding factors can provide valuable information for future PVP researchers.

To investigate the linear relationship between PVP and electrocardiogram (ECG) the waveforms were transformed into the frequency domain. A power spectral density was plotted, and the Pearson correlation coefficients were calculated for both preoperative and intraoperative settings. Linear regression models were computed for PVP and varying …

Novel Machine Learning And Wearable Sensor Based Solutions For Smart Healthcare Monitoring, Rajdeep Kumar Nath

Theses and Dissertations--Electrical and Computer Engineering

The advent of IoT has enabled the design of connected and integrated smart health monitoring systems. These health monitoring systems can be utilized for monitoring the mental and physical wellbeing of a person. Stress, anxiety, and hypertension are the major elements responsible for the plethora of physical and mental illnesses. In this context, the older population demands special attention because of the several age-related complications that exacerbate the effects of stress, anxiety, and hypertension. Monitoring stress, anxiety, and blood pressure regularly can prevent long-term damage by initiating necessary intervention or clinical treatment beforehand. This will improve the quality of life …

A Harmless Wireless Quantum Alternative To Cell Phones Based On Quantum Noise, Florentin Smarandache, Robert Neil Boyd, Victor Christianto

Branch Mathematics and Statistics Faculty and Staff Publications

In the meantime we know that 4G and 5G technologies cause many harms to human health. Therefore, here we submit a harmless wireless quantum alternative to cell phones. It is our hope that this alternative

Re-Annotation Of Cough Events In The Ami Corpus, Paul Leamy, Damon Berry, David Dorran, Ted Burke

Conference papers

Cough sounds act as an important indicator of an individual's physical health, often used by medical professionals in diagnosing a patient's ailments. In recent years progress has been made in the area of automatically detecting cough events and, in certain cases, automatically identifying the ailment associated with a particular cough sound. Ethical and sensitivity issues associated with audio recordings of coughs makes it more difficult for this data to be made publicly available. However, without the public availability of a reliable database of cough sounds, developments in the area of audio event detection are likely to be hampered. The purpose …

Graph Information Processing For Artificial Intelligence, Limeng Pu

LSU Doctoral Dissertations

In the last decade, techniques for artificial intelligence (AI) has advanced tremendously, which lead to solutions to many problems that have long-troubled us. Such examples include image/video recognition, speech recognition, and 3D scenario recognition. As the tool become more and more powerful, we started to explore data types that have never been handled in an AI fashion. Graph is undoubtedly the first one that comes to mind. Many important real-life data is or can be represented as graphs or networks: social networks, communication networks, protein-protein interaction networks, molecular structures, etc. Yet very little attention has been devoted to the study …

Portable Electrocardiogram Device And Signal Processing Design, Ryan F. Blaalid

Electrical Engineering

Full 12-lead electrocardiogram (ECG) measurements require inconvenient and time consuming adhesive electrode placement. This project proposes a design for a Bluetooth based ECG for remote patient measurement. The device is designed to measure up to 6-leads and utilizes 5 dry (non-adhesive) electrodes to accomplish this. The device delivers the ECG data to the user’s mobile smart phone and can then be sent to the patient’s doctor for analysis. Since the contact of the dry electrodes to the skin is not perfect, low-frequency noise called baseline wandering is introduced. A signal processing technique borrowed from image processing called morphological filtering is …

Eeg Classification Using Residual Neural Networks, Eren Esener

Electrical Engineering

There is a growing desire to understand the EEG (electroencephalogram) signals related with brain activities. In order to analyze EEG signals, they first must be measured by sensors, which induces a lot of noise; then these signals are classified to understand the intended actions. In many cases a neural network is used as the algorithms for classification. A residual neural network (ResNet) is an artificial neural network (ANN) of a kind that are related with the pyramidal cells in the cerebral cortex. The goal of this work is to investigate the viability of ResNets for classifying EEG signals for hand …

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 …

Extraction Of Vital Signs Using Real Time Video Analysis For Neonatal Monitoring, Bhushan Lohani

Electrical Engineering Theses

Video data is now commonly used for analysis in surveillance, security, medical and many other fields. The development of low cost but high-quality portable cameras has contributed significantly to this trend. One such trend includes non-invasive vital statistics monitoring of infants in Neonatal Intensive Care Units (NICU). National Center for Health Statistics Publications has reported a high infant death rate (23,215 in 2014). This statistic has drawn the interest of health system professionals. Due to occurrence of conditions like bradycardia, apnea and hypoxia, these preterm infants are kept in an NICU for constant monitoring. One of the problems faced at …

Frameworks To Investigate Robustness And Disease Characterization/Prediction Utility Of Time-Varying Functional Connectivity State Profiles Of The Human Brain At Rest, Anees Abrol

Electrical and Computer Engineering ETDs

Neuroimaging technologies aim at delineating the highly complex structural and functional organization of the human brain. In recent years, several unimodal as well as multimodal analyses of structural MRI (sMRI) and functional MRI (fMRI) neuroimaging modalities, leveraging advanced signal processing and machine learning based feature extraction algorithms, have opened new avenues in diagnosis of complex brain syndromes and neurocognitive disorders. Generically regarding these neuroimaging modalities as filtered, complimentary insights of brain’s anatomical and functional organization, multimodal data fusion efforts could enable more comprehensive mapping of brain structure and function.

Large scale functional organization of the brain is often studied by …

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 …

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 …

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 …

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 …

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 …

Eeg And Emg Sensorimotor Measurements To Assess Proprioception Following Acl Reconstruction, Teagan Frances Northrup

Honors Theses and Capstones

The Anterior Cruciate Ligament (ACL) is the primary source of rotational stability in the knee by preventing the tibia from sliding in front of the femur. When the ACL is torn, it typically must be repaired through reconstructive surgery which results in proprioceptive deficiencies in the knee. Proprioception plays an important role in understanding where one’s knee is in space, sensing movement and reacting accordingly. This study examines an alternative method of measuring proprioceptive responses to a stimulus (motion) by using electromyogram (EMG) and electroencephalogram (EEG) signals to observe muscle and brain activity. Two participants (one with an ACL reconstruction …

Self-Image Multimedia Technologies For Feedforward Observational Learning, Nkiruka M. A. Uzuegbunam

Theses and Dissertations--Electrical and Computer Engineering

This dissertation investigates the development and use of self-images in augmented reality systems for learning and learning-based activities. This work focuses on self- modeling, a particular form of learning, actively employed in various settings for therapy or teaching. In particular, this work aims to develop novel multimedia systems to support the display and rendering of augmented self-images. It aims to use interactivity (via games) as a means of obtaining imagery for use in creating augmented self-images. Two multimedia systems are developed, discussed and analyzed. The proposed systems are validated in terms of their technical innovation and their clinical efficacy in …