Biomedical Engineering and Bioengineering Commons^™

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.

On-Demand Electrically Induced Decomposition Of Thin-Film Nitrocellulose Membranes For Wearable Or Implantable Biosensor Systems, Benjamin M. Horstmann

Theses and Dissertations

Implantable or subcutaneous biosensors used for continuous health monitoring have a limited functional lifetime requiring frequent replacement and therefore may be highly discomforting to the patient and become costly. One possible solution to this problem is use of biosensor arrays where each individual reserve sensor can be activated on-demand when the previous one becomes inoperative due to biofouling or enzyme degradation. Each reserve biosensor in the array is housed in an individual Polydimethylsiloxane (PDMS) well and is protected from exposure to bodily fluids such as interstitial fluid ( ISF) by a thin-film nitrocellulose membrane. Controlled activation is achieved by decomposing …

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 …

Experimental And Model-Based Terahertz Imaging And Spectroscopy For Mice, Human, And Phantom Breast Cancer Tissues, Tyler Bowman

Graduate Theses and Dissertations

The goal of this work is to investigate terahertz technology for assessing the surgical margins of breast tumors through electromagnetic modeling and terahertz experiments. The measurements were conducted using a pulsed terahertz system that provides time and frequency domain signals. Three types of breast tissues were investigated in this work. The first was formalin-fixed, paraffin-embedded tissues from human infiltrating ductal and lobular carcinomas. The second was human tumors excised within 24-hours of lumpectomy or mastectomy surgeries. The third was xenograft and transgenic mice breast cancer tumors grown in a controlled laboratory environment to achieve more data for statistical analysis.

Experimental …

Computer-Aided Diagnoses (Cad) System: An Artificial Neural Network Approach To Mri Analysis And Diagnosis Of Alzheimer's Disease (Ad), Berizohar Padilla Cerezo

Master's Theses

Alzheimer’s disease (AD) is a chronic and progressive, irreversible syndrome that deteriorates the cognitive functions. Official death certificates of 2013 reported 84,767 deaths from Alzheimer’s disease, making it the 6th leading cause of death in the United States. The rate of AD is estimated to double by 2050. The neurodegeneration of AD occurs decades before symptoms of dementia are evident. Therefore, having an efficient methodology for the early and proper diagnosis can lead to more effective treatments.

Neuroimaging techniques such as magnetic resonance imaging (MRI) can detect changes in the brain of living subjects. Moreover, medical imaging techniques are the …

Understanding The Surface Fouling Mechanism Of Ultrananocrystalline Diamond Microelectrodes Using Microfluidics For Neurochemical Detection, An-Yi Chang

Doctoral Dissertations

Electrochemical methods are widely used for chronic neurochemical sensing, but thus far, the organic solution redox reactions fouled the electrodes' surface. It caused the reduction of sensitivity and the electrodes' lifetime.

Here, we present the boron-doped nanocrystalline diamond microelectrodes (BDUNCD) as the next generation electrode material for neurochemical sensor development. To aid in long-term chronic monitoring of neurochemicals, they have a wide window of electrochemical potential, extremely low background current, and excellent chemical inertness. The main research goal is to reduce the rate of electrode fouling due to the reaction by-products, and significantly extend their useful lifetime.

We systematically characterize …

Point Of Care Diagnostics And Health Monitoring Devices, Akshaya Shanmugam

Doctoral Dissertations

Existing disease screening methods mostly rely on symptom based diagnosis. This is mainly because of lack of accessibility and cost associated with the tests. Testing for the presence of the disease after the onset of symptoms has a negative impact on chances of survival and treatment costs. Miniaturized low cost diagnostic devices that can be used outside the hospital setting can provide continuous health monitoring and aid in early diagnosis. This thesis presents techniques to develop such disease screening and health monitoring devices. The techniques presented here focus on medical devices that can benefit from microfluidic devices, fluorescence imaging, and …

Wireless Monitoring Of Driver's Pulse Rate And Temperature Using Hand Gloves Approach, Rohith Reddy Narala

Graduate Theses and Dissertations

There is growing concern about dangers correlated with driving, for people with known cardiovascular diseases. However, the association between having a chronic cardiovascular disease and being involved in a motor vehicle crash remains controversial. This study aims to monitor people with known medical emergencies or other medical conditions while driving [1]. It also helps the co-passengers to be cautious while the person is driving with an abnormal health condition. Designed it to be convenient and also can be easily adaptable by the end user.

The proposed project focuses on a wearable sensor glove that equipped with a pulse rate sensor, …

Time-Frequency Analysis Of Intracardiac Electrogram, Erik Brockman

Master's Theses

The Cardiac Rhythm Management Division of St. Jude Medical specializes in the development of implantable cardioverter defibrillators that improve the quality of life for patients diagnosed with a variety of cardiac arrhythmias, especially for patients prone to sudden cardiac death. With the goal to improve detection of cardiac arrhythmias, this study explored the value in time-frequency analysis of intracardiac electrogram in four steps. The first two steps characterized, in the frequency domain, the waveforms that construct the cardiac cycle. The third step developed a new algorithm that putatively provides the least computationally expensive way to identifying cardiac waveforms in the …

Bottom-Up Design Of Artificial Neural Network For Single-Lead Electrocardiogram Beat And Rhythm Classification, Srikanth Thiagarajan

Doctoral Dissertations

Performance improvement in computerized Electrocardiogram (ECG) classification is vital to improve reliability in this life-saving technology. The non-linearly overlapping nature of the ECG classification task prevents the statistical and the syntactic procedures from reaching the maximum performance. A new approach, a neural network-based classification scheme, has been implemented in clinical ECG problems with much success. The focus, however, has been on narrow clinical problem domains and the implementations lacked engineering precision. An optimal utilization of frequency information was missing. This dissertation attempts to improve the accuracy of neural network-based single-lead (lead-II) ECG beat and rhythm classification. A bottom-up approach defined …