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Description
Photoplethysmography (PPG) is currently a leading and growing field of researchwithin the biomedical industry. With its primary use in pulse oximetry and capability of quickly, non-intrusively, evaluating essential vital signs like heart rate and oxygen levels. This thesis will explore the literature on new and innovative research in pulse oximetry. Then introduce PPG

Photoplethysmography (PPG) is currently a leading and growing field of researchwithin the biomedical industry. With its primary use in pulse oximetry and capability of quickly, non-intrusively, evaluating essential vital signs like heart rate and oxygen levels. This thesis will explore the literature on new and innovative research in pulse oximetry. Then introduce PPG signals including how to calculate heart rate, oxygen saturation, and current problems, mainly focused on motion artifacts. The development of hardware and software systems using Bluetooth to transmit data to MATLAB for algorithm processing. Testing different signal processing techniques and parameters evaluating their effects on algorithm accuracy and reduction of motion artifact. Using accelerometers to identify motion and apply filters to effectively reduce minor motion artifacts. Then perform real-time data analysis and algorithm processing resulting in heart rate and oxygen level calculations.
ContributorsMuhn, George (Author) / Redkar, Sangram (Thesis advisor) / Nichols, Kevin (Committee member) / Subramanian, Susheelkumar (Committee member) / Arizona State University (Publisher)
Created2022
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Description
With more people falling every year it is more important to continue to track everyday activity as well as follow the progress that someone is making over time. As well as at risk subjects, athletes are also wanting to track their activity as well as improve in finer control of

With more people falling every year it is more important to continue to track everyday activity as well as follow the progress that someone is making over time. As well as at risk subjects, athletes are also wanting to track their activity as well as improve in finer control of their motions and abilities. To improve someone’s balance, strength, flexibility, and more someone can now start to use different biological sensors to help live a healthier and better lifestyle. To build different sensors requires materials that are comfortable to wear and accurate in collecting data. Graphene has been considered a wonder material that is used in many different applications which allow circuits and devices to use the flexible and durable material to conduct electricity. This paper shows multiple different tests and 36 trials of using graphene as a device which measures pressure that can be used to analyze gait patterns. These tests involve walking on a dual force plate treadmill for 90 continuous seconds with the graphene strip in the heel of the shoe wirelessly transmitting data to be recorded. The initial tests show that graphene will pick up noise and that graphene can start to deteriorate without proper protection. When looking at subject 1 there is less than .01 seconds of error between the graphene circuit and the ground truth. The ground truth was collected simultaneously, and the t-tests and ANOVA tests showed that there is no statistical difference between the graphene system and the ground truth. These tests also showed a 96.7% reproducibility score. There are limitations as seen in the later subjects, but these limitations can be overcome by further protecting the graphene and replacing the strip when it starts to show signs of deterioration which will allow graphene to be used in everyday bio wearable devices.
ContributorsSweeten, William (Author) / Lockhart, Thurmon (Thesis advisor) / Arquiza, Jose Apollo (Committee member) / Soangra, Rahul (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Stroke is the leading cause of long-term disability in the U.S., with up to 60% of strokescausing speech loss. Individuals with severe stroke, who require the most frequent, intense speech therapy, often cannot adhere to treatments due to high cost and low success rates. Therefore, the ability to make functionally

Stroke is the leading cause of long-term disability in the U.S., with up to 60% of strokescausing speech loss. Individuals with severe stroke, who require the most frequent, intense speech therapy, often cannot adhere to treatments due to high cost and low success rates. Therefore, the ability to make functionally significant changes in individuals with severe post- stroke aphasia remains a key challenge for the rehabilitation community. This dissertation aimed to evaluate the efficacy of Startle Adjuvant Rehabilitation Therapy (START), a tele-enabled, low- cost treatment, to improve quality of life and speech in individuals with severe-to-moderate stroke. START is the exposure to startling acoustic stimuli during practice of motor tasks in individuals with stroke. START increases the speed and intensity of practice in severely impaired post-stroke reaching, with START eliciting muscle activity 2-3 times higher than maximum voluntary contraction. Voluntary reaching distance, onset, and final accuracy increased after a session of START, suggesting a rehabilitative effect. However, START has not been evaluated during impaired speech. The objective of this study is to determine if impaired speech can be elicited by startling acoustic stimuli, and if three days of START training can enhance clinical measures of moderate to severe post-stroke aphasia and apraxia of speech. This dissertation evaluates START in 42 individuals with post-stroke speech impairment via telehealth in a Phase 0 clinical trial. Results suggest that impaired speech can be elicited by startling acoustic stimuli and that START benefits individuals with severe-to-moderate post-stroke impairments in both linguistic and motor speech domains. This fills an important gap in aphasia care, as many speech therapies remain ineffective and financially inaccessible for patients with severe deficits. START is effective, remotely delivered, and may likely serve as an affordable adjuvant to traditional therapy for those that have poor access to quality care.
ContributorsSwann, Zoe Elisabeth (Author) / Honeycutt, Claire F (Thesis advisor) / Daliri, Ayoub (Committee member) / Rogalsky, Corianne (Committee member) / Liss, Julie (Committee member) / Schaefer, Sydney (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Finite element models (FEMs) of spine segments validated in their intact states are often used to make predictions following structural modifications simulating surgical procedures, including posterior fusion with pedicle screws and rods (PSR) and laminectomy (removal of posterior column bone to decompress the spinal cord). The gold standard for spine

Finite element models (FEMs) of spine segments validated in their intact states are often used to make predictions following structural modifications simulating surgical procedures, including posterior fusion with pedicle screws and rods (PSR) and laminectomy (removal of posterior column bone to decompress the spinal cord). The gold standard for spine FEM validation compares predicted vs. experimental intervertebral ranges of motion (ROM). Given that muscle co-contraction compresses the spine, validation that considers compression may produce a more robust FEM. One research goal was to evaluate an experimental method of compressing a lumbar spine segment through its sagittal plane balance (pivot) point (BP) using a 6DOF robotic test system. Experimental data supported the hypothesis that structural modifications, such as PSR and laminectomy alter the segment’s BP location and its compressive stiffness. However, evaluation showed that the experimental BP method is sensitive to specimen posture in the robotic test frame; slight flexion or extension produced shear loads during compression that affect BP location and should be included in specimen-specific FEMs to ensure similar load conditions. Another goal was to develop a uniquely calibrated specimen-specific FEM of an intact L4-5 motion segment using the experimental BP data. A specimen-specific FEM was created and calibrated using experimental BP compressive stiffness data, however matching experimental BP location data was unsuccessful. The BP-compression calibrated FEM was evaluated by comparing predicted responses to loads following simulated PSR and laminectomy to specimen-specific experimental data. Predictions using the BP-calibrated and ROM-calibrated FEMs were compared. The BP-calibration process helped identify an unrealistic FEM disc geometry (nucleus pulposus size and location). Both BP-compression and ROM-calibrated FEMs predicted effects of PSR on stiffness (compressive and flexural) that were greater than experimental, which helped identify a problem with simplified representations of bone in the posterior column and at the anterior column interface. The BP-compression calibrated FEMs predicted relative shifts in BP locations and bone surface strains during compression that were closer to experimental data than similarly modified ROM-calibrated FEMs. Collectively, these results support the use of BP measures in experimental and model-based investigations of surgical modifications of the spine.
ContributorsSawa, Anna Genowefa Ulrika (Author) / Abbas, James (Thesis advisor) / Crawford, Neil R (Thesis advisor) / Kelly, Brian P (Committee member) / Helms-Tillery, Stephen (Committee member) / Sadleir, Rosalind (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Non-invasive biosensors enable rapid, real-time measurement and quantification of biological processes, such as metabolic state. Currently, the most accurate metabolic sensors are invasive, and significant cost is required, with few exceptions, to achieve similar accuracy using non-invasive methods. This research, conducted within the Biodesign Institute Center for Bioelectronics and Biosensors,

Non-invasive biosensors enable rapid, real-time measurement and quantification of biological processes, such as metabolic state. Currently, the most accurate metabolic sensors are invasive, and significant cost is required, with few exceptions, to achieve similar accuracy using non-invasive methods. This research, conducted within the Biodesign Institute Center for Bioelectronics and Biosensors, leverages the selective reactivity of a chemical sensing solution to develop a sensor which measures acetone in the breath for ketosis and ketoacidosis diagnostics, which is relevant to body weight management and type I diabetes. The sensor displays a gradient of color changes, and the absorbance change is proportional to the acetone concentration in the part- per-million range, making applicable for detection ketosis and ketoacidosis in human breath samples. The colorimetric sensor response can be fitted to a Langmuir-like model for sensor calibration. The sensors best performance comes with turbulent, continuous exposure to the samples, rather than batch sample exposure. With that configuration, these novel sensors offer significant improvements to clinical and at- home measurement of ketosis and ketoacidosis.
ContributorsDenham, Landon (Author) / Forzani, Erica (Thesis advisor) / Wang, Shaopeng (Committee member) / Kulick, Doina (Committee member) / Arizona State University (Publisher)
Created2023
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Description
The use of mRNA for therapeutic purposes has gained significant attention due to its potential to treat a wide range of diseases, including cancer, infectious diseases, and genetic disorders. However, the efficient delivery of mRNA to target cells remains a major challenge, and delivery of mRNA faces major issues such

The use of mRNA for therapeutic purposes has gained significant attention due to its potential to treat a wide range of diseases, including cancer, infectious diseases, and genetic disorders. However, the efficient delivery of mRNA to target cells remains a major challenge, and delivery of mRNA faces major issues such as rapid degradation and poor cellular uptake. Aminoglycoside-derived lipopolymer nanoparticles (LPNs) have been shown as a promising platform for plasmid DNA (pDNA) delivery due to their stability, biocompatibility, and ability to encapsulate mRNA. The current study aims to develop and optimize LPNs formulation for the delivery of mRNA in aggressive cancer cells, using a combination of chemical synthesis, physicochemical characterization, and in vitro biological assays. From a small library of aminoglycoside-derived lipopolymers, the lead lipopolymers were screened for the efficient delivery of mRNA. The complexes were synthesized with different ratios of lipopolymers to mRNA. The appropriate binding ratios of lipopolymers and mRNA were determined by gel electrophoresis. The complexes were characterized using dynamic light scattering (DLS) and zeta potential. The transgene expression efficacy of polymers was evaluated using in vitro bioluminescence assay. The toxicity of LPNs and LPNs-mRNA complexes was evaluated using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The current study comprehensively investigates the optimization of the LPNs-mRNA formulation for enhanced efficacy in transgene expression in human advanced-stage melanoma cell lines.
ContributorsWubhayavedantapuram, Revanth (Author) / Rege, Kaushal (Thesis advisor) / Acharya, Abhinav (Committee member) / Yaron, Jordan (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Photoplethysmography (PPG) is a noninvasive optical signal that measures the change in blood volume. This particular signal can be interpreted to yield heart rate (HR) information which is commonly used in medical settings and diagnostics through wearable devices. The noninvasive nature of the measurement of the signal however causes it

Photoplethysmography (PPG) is a noninvasive optical signal that measures the change in blood volume. This particular signal can be interpreted to yield heart rate (HR) information which is commonly used in medical settings and diagnostics through wearable devices. The noninvasive nature of the measurement of the signal however causes it to be susceptible to noise sources such as motion artifacts (MA). This research starts by describing an end-to-end embedded HR estimation system that leverages noisy PPG and accelerometer data through machine learning (ML) to estimate HR. Through embedded ML for HR estimation, the limitations and challenges are highlighted, and a different HR estimation method is proposed. Next, a point-based value iteration (PBVI) framework is proposed to optimally select HR estimation filters based on the observed user activity. Lastly, the underlying dynamics of the PPG are explored in order to create a sparse dynamic expression of the PPG signal, which can be used to simulate PPG data to improve ML or remove MA from PPG.
ContributorsSindorf, Jacob (Author) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / Phatak, Amar (Committee member) / Arizona State University (Publisher)
Created2023
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Description
While wearable soft robots have successfully addressed many inherent design limitations faced by wearable rigid robots, they possess a unique set of challenges due to their soft and compliant nature. Some of these challenges are present in the sensing, modeling, control and evaluation of wearable soft robots. Machine learning algorithms

While wearable soft robots have successfully addressed many inherent design limitations faced by wearable rigid robots, they possess a unique set of challenges due to their soft and compliant nature. Some of these challenges are present in the sensing, modeling, control and evaluation of wearable soft robots. Machine learning algorithms have shown promising results for sensor fusion with wearable robots, however, they require extensive data to train models for different users and experimental conditions. Modeling soft sensors and actuators require characterizing non-linearity and hysteresis, which complicates deriving an analytical model. Experimental characterization can capture the characteristics of non-linearity and hysteresis but requires developing a synthesized model for real-time control. Controllers for wearable soft robots must be robust to compensate for unknown disturbances that arise from the soft robot and its interaction with the user. Since developing dynamic models for soft robots is complex, inaccuracies that arise from the unmodeled dynamics lead to significant disturbances that the controller needs to compensate for. In addition, obtaining a physical model of the human-robot interaction is complex due to unknown human dynamics during walking. Finally, the performance of soft robots for wearable applications requires extensive experimental evaluation to analyze the benefits for the user. To address these challenges, this dissertation focuses on the sensing, modeling, control and evaluation of soft robots for wearable applications. A model-based sensor fusion algorithm is proposed to improve the estimation of human joint kinematics, with a soft flexible robot that requires compact and lightweight sensors. To overcome limitations with rigid sensors, an inflatable soft haptic sensor is developed to enable gait sensing and haptic feedback. Through experimental characterization, a mathematical model is derived to quantify the user's ground reaction forces and the delivered haptic force. Lastly, the performance of a wearable soft exosuit in assisting human users during lifting tasks is evaluated, and the benefits obtained from the soft robot assistance are analyzed.
ContributorsQuiñones Yumbla, Emiliano (Author) / Zhang, Wenlong (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamid (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Magnetic resonance imaging (MRI) is the most powerful instrument for imaging anatomical structures. One of the most essential components of the MRI scanner is a radiofrequency (RF) coil. It induces resonant phenomena and receives the resonated RF signal from the body. Then, the signal is computed and reconstructed for MR

Magnetic resonance imaging (MRI) is the most powerful instrument for imaging anatomical structures. One of the most essential components of the MRI scanner is a radiofrequency (RF) coil. It induces resonant phenomena and receives the resonated RF signal from the body. Then, the signal is computed and reconstructed for MR images. Therefore, improving image quality by increasing the receiver's (Rx) efficiency is always remarkable. This research introduces a flexible and stretchable receive RF coil embedded in a dielectric-loaded material. Recent studies show that the adaptable coil can improve imaging quality by flexing and stretching to fit well with the sample's surface, reducing the spatial distance between the load and the coil. High permittivity dielectric material positioned between the coil and phantom was known to increase the RF field distribution's efficiency significantly. Recent studies integrating the high dielectric material with the coil show a significant improvement in signal-to-noise ratio (SNR), which can improve the overall efficiency of the coil. Previous research also introduced new elastic dielectric material, which shows improvement in uniformity when incorporated with an RF coil. Combining the adaptable RF coil with the elastic dielectric material has the potential to enhance the coil's performance further. The flexible dielectric material's limitations and unknown interaction with the coil pose a challenge. Thus, each component was integrated into a simple loop coil step-by-step, which allowed for experimentation and evaluation of the performance of each part. The mechanical performance was tested manually. The introduced coil is highly flexible and can stretch up to 20% of its original length in one direction. The electrical performance was evaluated in simulations and experiments on a 9.4T MRI scanner compared to conventional RF coils.
ContributorsHerabut, Chavalchart (Author) / Sohn, SungMin (Thesis advisor) / Sadleir, Rosalind (Committee member) / Beeman, Scott (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Magnetic Resonance Imaging has become an increasingly reliable source of medical imaging to obtain high quality detailed images of the human anatomy. Application specific coil or an array of coils when placed closely to the anatomy produces high quality image due to the improved spatial signal to noise ratio. Elastic

Magnetic Resonance Imaging has become an increasingly reliable source of medical imaging to obtain high quality detailed images of the human anatomy. Application specific coil or an array of coils when placed closely to the anatomy produces high quality image due to the improved spatial signal to noise ratio. Elastic RF coils have been shown to conform to the shape of the patient’s body and drastically reduce the gap between coil and anatomy. First, a major challenge faced by these elastic RF coils is the changing impedance condition as the coil takes a different shape for every individual. Next, an area that could benefit from the improved image quality and patient comfort that comes from flexible RF coil design is endorectal prostate imaging. Demonstrated in the first part of this dissertation is a modular solution to compensate the impedance mismatch. Standalone Wireless Impedance Matching (SWIM) system is an automatic impedance mismatch compensation system that can function independently of the MR scanner. The matching network consists of a capacitor array with RF switches to electronically cycle through different input impedance conditions. The SWIM system can automatically calibrate an RF coil in 3s with a reflection coefficient of less than -15dB resulting in improved Signal-to-noise ratio (SNR) of the sample image by 12% - 24%, based on sample size, when compared to a loaded coil without retuning. For the second part, we propose a novel elastic and inflatable RF coil integrated with the SWIM system for endorectal prostate imaging at 9.4T. A silicone polymer substrate filled with liquid metal alloy is designed and fabricated with a cavity to create ii inflation. This inflatable RF coil is combined with the SWIM system to automatically tune and match after inflating the RF coil for individual levels of inflation. The imaging results have shown a ~10%, ~19%, and ~25 % increase in SNR due to inflation of RF coil at different ROIs in the acquired image. Overall, the methods proposed and discussed in this thesis are a step towards a new generation of RF coil systems for both existing applications and upcoming ones.
ContributorsKandala, Sri Kirthi (Author) / Sohn, Sung-Min (Thesis advisor) / Kdibagkar, Vikram (Committee member) / Sadleir, Rosalind J (Committee member) / Beeman, Scott (Committee member) / Trichopoulos, Georgios (Committee member) / Arizona State University (Publisher)
Created2023