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Full-Text Articles in Biomedical Engineering and Bioengineering

Low Impedance, Durable, Self-Adhesive Hydrogel Epidermal Electrodes For Electrophysiology Recording, Naiyan Wu Apr 2024

Low Impedance, Durable, Self-Adhesive Hydrogel Epidermal Electrodes For Electrophysiology Recording, Naiyan Wu

McKelvey School of Engineering Theses & Dissertations

Traditional electrodes used for electrophysiology recording, characterized by their hard, dry, and inanimate nature, are fundamentally mismatched with the soft, moist, and bioactive characteristics of biological tissues, leading to suboptimal skin-electrode interfaces. Hydrogel materials, mirroring the high water content and biocompatibility of biological tissues, emerge as promising candidates for epidermal electronic materials due to their adjustable physicochemical properties. However, challenges such as inadequate electrical conductivity, elevated skin impedance, unreliable adhesion in moist conditions, and performance decline from dehydration have significantly restricted the efficacy and applicability of hydrogel-based electrodes. In this thesis, we report a high-performance hydrogel epidermal electrode patch for …


Long-Term Neural Activity Recorders Using Energy-Based Sensing, Compressive Computation And Data Logging, Darshit Mehta Aug 2021

Long-Term Neural Activity Recorders Using Energy-Based Sensing, Compressive Computation And Data Logging, Darshit Mehta

McKelvey School of Engineering Theses & Dissertations

Insects are ideal candidates for developing bio-robotic systems owing to their ability to thrive in almost any environment. For example, neurons in their exquisite olfactory sensory systems can be tapped to create a sensing platform for standoff chemical monitoring. However, for enabling such cyborg systems, it is vital that the neural activity of a freely behaving organism can be measured for long periods of time. The current state-of-the-art neural recording techniques are power-intensive and they either need batteries, which make them too bulky for insects, or they have to maintain a continuous telemetry link to an external power source which …


Deep Learning For Task-Based Image Quality Assessment In Medical Imaging, Weimin Zhou Jan 2021

Deep Learning For Task-Based Image Quality Assessment In Medical Imaging, Weimin Zhou

McKelvey School of Engineering Theses & Dissertations

It has been advocated to use objective measures of image quality (IQ) for assessing and optimizing medical imaging systems. Objective measures of IQ quantify the performance of an observer at a specific diagnostic task. Binary signal detection tasks and joint signal detection and localization (detection-localization) tasks are commonly considered in medical imaging. When optimizing imaging systems for binary signal detection tasks, the performance of the Bayesian Ideal Observer (IO) has been advocated for use as a figure-of-merit (FOM). The IO maximizes the observer performance that is summarized by the receiver operating characteristic (ROC) curve. When signal detection-localization tasks are considered, …


Theory, Design And Implementation Of Energy-Efficient Biotelemetry Using Ultrasound Imaging, Sri Harsha Kondapalli Jan 2021

Theory, Design And Implementation Of Energy-Efficient Biotelemetry Using Ultrasound Imaging, Sri Harsha Kondapalli

McKelvey School of Engineering Theses & Dissertations

This dissertation investigates the fundamental limits of energy dissipation in establishing a communication link with implantable medical devices using ultrasound imaging-based biotelemetry.

Ultrasound imaging technology has undergone a revolution during the last decade due to two primary innovations: advances in ultrasonic transducers that can operate over a broad range of frequencies and progresses in high-speed, high-resolution analog-to-digital converters and signal processors. Existing clinical and FDA approved bench-top ultrasound systems cangenerate real-time high-resolution images at frame rates as high as 10000 frames per second. On the other end of the spectrum, portable and hand-held ultrasound systems can generate high-speed real-time scans, …


A Modular Approach For Modeling, Detecting, And Tracking Freezing Of Gait In Parkinson Disease Using Inertial Sensors, Prateek Gundannavar Vijay Aug 2019

A Modular Approach For Modeling, Detecting, And Tracking Freezing Of Gait In Parkinson Disease Using Inertial Sensors, Prateek Gundannavar Vijay

McKelvey School of Engineering Theses & Dissertations

Parkinson disease, the second most common neurodegenerative disorder, is caused by the loss of dopaminergic subcortical neurons. Approximately 50% of people with Parkinson disease experience freezing of gait (FOG), a brief, episodic absence or marked reduction of forward progression of the feet despite the intention to walk. FOG causes falls and is resistant to medication in more than 50% of cases. FOG episodes can often be interrupted by mechanical interventions (e.g., a verbal reminder to march), but it is often not practical to apply these interventions on demand (e.g., there is not usually another person to detect an FOG episode …


Basis Vector Model Method For Proton Stopping Power Estimation Using Dual-Energy Computed Tomography, Shuangyue Zhang Dec 2018

Basis Vector Model Method For Proton Stopping Power Estimation Using Dual-Energy Computed Tomography, Shuangyue Zhang

McKelvey School of Engineering Theses & Dissertations

Accurate estimation of the proton stopping power ratio (SPR) is important for treatment planning and dose prediction for proton beam therapy. The state-of-the-art clinical practice for estimating patient-specific SPR distributions is the stoichiometric calibration method using single-energy computed tomography (SECT) images, which in principle may introduce large intrinsic uncertainties into estimation results. One major factor that limits the performance of SECT-based methods is the Hounsfield unit (HU) degeneracy in the presence of tissue composition variations. Dual-energy computed tomography (DECT) has shown the potential of reducing uncertainties in proton SPR prediction via scanning the patient with two different source energy spectra. …


Forward Electrophysiological Modeling And Inverse Problem For Uterine Contractions During Pregnancy, Mengxue Zhang Aug 2018

Forward Electrophysiological Modeling And Inverse Problem For Uterine Contractions During Pregnancy, Mengxue Zhang

McKelvey School of Engineering Theses & Dissertations

Uterine contractile dysfunction during pregnancy is a significant healthcare challenge that imposes heavy medical and financial burdens on both human beings and society. In the U.S., about 12% of babies are born prematurely each year, which is a leading cause of neonatal mortality and increases the possibility of having subsequent health problems. Post-term birth, in which a baby is born after 42 weeks of gestation, can cause risks for both the newborn and the mother. Currently, there is a limited understanding of how the uterus transitions from quiescence to excitation, which hampers our ability to detect labor and treat major …


Functional Electrical Stimulation Of Peripheral Nerve Tissue Via Regenerative Sieve Microelectrodes, Matthew Reagan Macewan May 2018

Functional Electrical Stimulation Of Peripheral Nerve Tissue Via Regenerative Sieve Microelectrodes, Matthew Reagan Macewan

McKelvey School of Engineering Theses & Dissertations

Functional electrical stimulation (FES) of peripheral nervous tissue offers a promising method for restoring motor function in patients suffering from complex neurological injuries. However, existing microelectrodes designed to stimulate peripheral nerve are unable to provide the type of stable, selective interface required to achieve near-physiologic control of peripheral motor axons and distal musculature. Regenerative sieve electrodes offer a unique alternative to such devices, achieving a highly stable, selective electrical interface with independent groups of regenerated nerve fibers integrated into the electrode. Yet, the capability of sieve electrodes to functionally recruit regenerated motor axons for the purpose of muscle activation remains …


Reconstruction Algorithms For Novel Joint Imaging Techniques In Pet, Homayoon Ranjbar Dec 2017

Reconstruction Algorithms For Novel Joint Imaging Techniques In Pet, Homayoon Ranjbar

McKelvey School of Engineering Theses & Dissertations

Positron emission tomography (PET) is an important functional in vivo imaging modality with many clinical applications. Its enormously wide range of applications has made both research and industry combine it with other imaging modalities such as X-ray computed tomography (CT) or magnetic resonance imaging (MRI). The general purpose of this work is to study two cases in PET where the goal is to perform image reconstruction jointly on two data types.

The first case is the Beta-Gamma image reconstruction. Positron emitting isotopes, such as 11C, 13N, and 18F, can be used to label molecules, and tracers, such …


Bio-Inspired Multi-Spectral And Polarization Imaging Sensors For Image-Guided Surgery, Nimrod Missael Garcia Dec 2017

Bio-Inspired Multi-Spectral And Polarization Imaging Sensors For Image-Guided Surgery, Nimrod Missael Garcia

McKelvey School of Engineering Theses & Dissertations

Image-guided surgery (IGS) can enhance cancer treatment by decreasing, and ideally eliminating, positive tumor margins and iatrogenic damage to healthy tissue. Current state-of-the-art near-infrared fluorescence imaging systems are bulky, costly, lack sensitivity under surgical illumination, and lack co-registration accuracy between multimodal images. As a result, an overwhelming majority of physicians still rely on their unaided eyes and palpation as the primary sensing modalities to distinguish cancerous from healthy tissue. In my thesis, I have addressed these challenges in IGC by mimicking the visual systems of several animals to construct low power, compact and highly sensitive multi-spectral and color-polarization sensors. I …