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The recording of biosignals enables physicians to correctly diagnose diseases and prescribe treatment. Existing wireless systems failed to effectively replace the conventional wired methods due to their large sizes, high power consumption, and the need to replace batteries. This thesis aims to alleviate these issues by presenting a series of

The recording of biosignals enables physicians to correctly diagnose diseases and prescribe treatment. Existing wireless systems failed to effectively replace the conventional wired methods due to their large sizes, high power consumption, and the need to replace batteries. This thesis aims to alleviate these issues by presenting a series of wireless fully-passive sensors for the acquisition of biosignals: including neuropotential, biopotential, intracranial pressure (ICP), in addition to a stimulator for the pacing of engineered cardiac cells. In contrast to existing wireless biosignal recording systems, the proposed wireless sensors do not contain batteries or high-power electronics such as amplifiers or digital circuitries. Instead, the RFID tag-like sensors utilize a unique radiofrequency (RF) backscattering mechanism to enable wireless and battery-free telemetry of biosignals with extremely low power consumption. This characteristic minimizes the risk of heat-induced tissue damage and avoids the need to use any transcranial/transcutaneous wires, and thus significantly enhances long-term safety and reliability. For neuropotential recording, a small (9mm x 8mm), biocompatible, and flexible wireless recorder is developed and verified by in vivo acquisition of two types of neural signals, the somatosensory evoked potential (SSEP) and interictal epileptic discharges (IEDs). For wireless multichannel neural recording, a novel time-multiplexed multichannel recording method based on an inductor-capacitor delay circuit is presented and tested, realizing simultaneous wireless recording from 11 channels in a completely passive manner. For biopotential recording, a wearable and flexible wireless sensor is developed, achieving real-time wireless acquisition of ECG, EMG, and EOG signals. For ICP monitoring, a very small (5mm x 4mm) wireless ICP sensor is designed and verified both in vitro through a benchtop setup and in vivo through real-time ICP recording in rats. Finally, for cardiac cell stimulation, a flexible wireless passive stimulator, capable of delivering stimulation current as high as 60 mA, is developed, demonstrating successful control over the contraction of engineered cardiac cells. The studies conducted in this thesis provide information and guidance for future translation of wireless fully-passive telemetry methods into actual clinical application, especially in the field of implantable and wearable electronics.
ContributorsLiu, Shiyi (Author) / Christen, Jennifer (Thesis advisor) / Nikkhah, Mehdi (Committee member) / Phillips, Stephen (Committee member) / Cao, Yu (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Stroke is a debilitating disorder and 75% of individuals with stroke (iwS) have upper extremity deficits. IwS are prescribed therapies to enhance upper-extremity mobility, but current most effective therapies have minimum requirements that the individuals with severe impairment do not meet. Thus, there is a need to enhance the therapies.

Stroke is a debilitating disorder and 75% of individuals with stroke (iwS) have upper extremity deficits. IwS are prescribed therapies to enhance upper-extremity mobility, but current most effective therapies have minimum requirements that the individuals with severe impairment do not meet. Thus, there is a need to enhance the therapies. Recent studies have shown that StartReact -the involuntary release of a planned movement, triggered by a startling stimulus (e.g., loud sound)- elicits faster and larger muscle activation in iwS compared to voluntary-initiated movement. However, StartReact has been only cursorily studied to date and there are some gaps in the StartReact knowledge. Previous studies have only evaluated StartReact on single-jointed movements in iwS, ignoring more functional tasks. IwS usually have abnormal flexor activity during extension tasks and abnormal muscle synergy especially during multi-jointed tasks; therefore, it is unknown 1) if more complex multi-jointed reach movements are susceptible to StartReact, and 2) if StartReact multi-jointed movements will be enhanced in the same way as single-jointed movements in iwS. In addition, previous studies showed that individuals with severe stroke, especially those with higher spasticity, experienced higher abnormal flexor muscle activation during StartReact trials. However, there is no study evaluating the impact of this elevated abnormal flexor activity on movement, muscle activation and muscle synergy alterations during voluntary-initiated movements after exposure to StartReact.
This dissertation evaluates StartReact and the voluntary trials before and after exposure to StartReact during a point-to-point multi-jointed reach task to three different targets covering a large workspace. The results show that multi-jointed reach tasks are susceptible to StartReact in iwS and the distance, muscle and movement onset speed, and muscle activations percentages and amplitude increase during StartReact trials. In addition, the distance, accuracy, muscle and movement onsets speeds, and muscle synergy similarity indices to the norm synergies increase during the voluntary-initiated trials after exposure to StartReact. Overall, this dissertation shows that exposure to StartReact did not impair voluntary-initiated movement and muscle synergy, but even improved them. Therefore, this study suggests that StartReact is safe for more investigations in training studies and therapy.
ContributorsRahimiTouranposhti, Marziye (Author) / Honeycutt, Claire F. (Thesis advisor) / Roh, Jinsook (Committee member) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamid (Committee member) / Schaefer, Sydney (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Traditionally, wearable exoskeletons for gait assistance have addressed the issue of high power requirement of providing support during walking. However, exoskeletons often are bulky, and suffer from misalignment of joints between the robot and the user. Soft robots in recent work have shown the ability to provide a high degree

Traditionally, wearable exoskeletons for gait assistance have addressed the issue of high power requirement of providing support during walking. However, exoskeletons often are bulky, and suffer from misalignment of joints between the robot and the user. Soft robots in recent work have shown the ability to provide a high degree of compliance with a light weight and lower cost. This work presents the design, control, and evaluation of a soft inflatable exosuit to assist knee extension. First, the design of novel soft inflatable actuators of I cross-section and their application in the soft inflatable exosuit is presented. The actuators are applied to a soft and lightweight garment interface to assist in knee extension during the swing phase demonstrating reduced muscle activity for the quadriceps. Second, the control of the soft exosuit is presented with the introduction of a knee angle measurement system and smart shoe insole sensors. A new control method using human joint stiffness models as well as actuator models is developed. The new control method is evaluated with three users and a reduction in the sEMG activity of the quadriceps is observed with an increase in the activity of the hamstrings. Third, an improved version of the exosuit and a controller to assist knee extension in swing phase and initial stance are presented. The exosuit is applied to seven healthy and three impaired participants. Kinematics, muscle activity and gait compensations are studied. Reduced muscle activity for the quadriceps is seen in healthy participants with reduced execution times for functional activities such as timed up-and-go as well as sit-to-stand transitions in impaired participants. Finally, an untethered version of the soft exosuit using inflatable actuator composites and a portable pneumatic source are presented. Finite element models for the composites and inflatable actuators are generated and the actuators are characterized for performance. The design of a portable source for the exosuit is also presented. The inflatable actuator composites and the portable source are implemented in a portable exosuit system which demonstrated a reduction in the Vastus Lateralis activity during incline walking for three participants. Overall, this work investigated the feasibility of several versions of the soft exosuit for gait assistance.
ContributorsSridar, Saivimal (Author) / Zhang, Wenlong (Thesis advisor) / Sugar, Thomas (Committee member) / Lockhart, Thurmon (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Traumatic brain injury (TBI) affects an estimated 1.7 million people in the United States each year and is a leading cause of death and disability for children and young adults in industrialized countries. Unfortunately, the molecular and cellular mechanisms of injury progression have yet to be fully elucidated. Consequently, this

Traumatic brain injury (TBI) affects an estimated 1.7 million people in the United States each year and is a leading cause of death and disability for children and young adults in industrialized countries. Unfortunately, the molecular and cellular mechanisms of injury progression have yet to be fully elucidated. Consequently, this complexity impacts the development of accurate diagnosis and treatment options. Biomarkers, objective signatures of injury, can inform and facilitate development of sensitive and specific theranostic devices. Discovery techniques that take advantage of mining the temporal complexity of TBI are critical for the identification of high specificity biomarkers.

Domain antibody fragment (dAb) phage display, a powerful screening technique to uncover protein-protein interactions, has been applied to biomarker discovery in various cancers and more recently, neurological conditions such as Alzheimer’s Disease and stroke. The small size of dAbs (12-15 kDa) and ability to screen against brain vasculature make them ideal for interacting with the neural milieu in vivo. Despite these characteristics, implementation of dAb phage display to elucidate temporal mechanisms of TBI has yet to reach its full potential.

My dissertation employs a unique target identification pipeline that entails in vivo dAb phage display and next generation sequencing (NGS) analysis to screen for temporal biomarkers of TBI. Using a mouse model of controlled cortical impact (CCI) injury, targeting motifs were designed based on the heavy complementarity determining region (HCDR3) structure of dAbs with preferential binding to acute (1 day) and subacute (7 days) post-injury timepoints. Bioreactivity for these two constructs was validated via immunohistochemistry. Further, immunoprecipitation-mass spectrometry analysis identified temporally distinct candidate biological targets in brain tissue lysate.

The pipeline of phage display followed by NGS analysis demonstrated a unique approach to discover motifs that are sensitive to the heterogeneous and diverse pathology caused by neural injury. This strategy successfully achieves 1) target motif identification for TBI at distinct timepoints and 2) characterization of their spatiotemporal specificity.
ContributorsMartinez, Briana Isabella (Author) / Stabenfeldt, Sarah E (Thesis advisor) / Lifshitz, Jonathan (Committee member) / Sierks, Michael (Committee member) / Kleim, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2020
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Description
One of the single-most insightful, and visionary talks of the 20th century, “There’s plenty of room at the bottom,” by Dr. Richard Feynman, represented a first foray into the micro- and nano-worlds of biology and chemistry with the intention of direct manipulation of their individual components. Even so, for decades

One of the single-most insightful, and visionary talks of the 20th century, “There’s plenty of room at the bottom,” by Dr. Richard Feynman, represented a first foray into the micro- and nano-worlds of biology and chemistry with the intention of direct manipulation of their individual components. Even so, for decades there has existed a gulf between the bottom-up molecular worlds of biology and chemistry, and the top-down world of nanofabrication. Creating single molecule nanoarrays at the limit of diffraction could incentivize a paradigm shift for experimental assays. However, such arrays have been nearly impossible to fabricate since current nanofabrication tools lack the resolution required for precise single-molecule spatial manipulation. What if there existed a molecule which could act as a bridge between these top-down and bottom-up worlds?

At ~100-nm, a DNA origami macromolecule represents one such bridge, acting as a breadboard for the decoration of single molecules with 3-5 nm resolution. It relies on the programmed self-assembly of a long, scaffold strand into arbitrary 2D or 3D structures guided via approximately two hundred, short, staple strands. Once synthesized, this nanostructure falls in the spatial manipulation regime of a nanofabrication tool such as electron-beam lithography (EBL), facilitating its high efficiency immobilization in predetermined binding sites on an experimentally relevant substrate. This placement technology, however, is expensive and requires specialized training, thereby limiting accessibility.

The work described here introduces a method for bench-top, cleanroom/lithography-free, DNA origami placement in meso-to-macro-scale grids using tunable colloidal nanosphere masks, and organosilane-based surface chemistry modification. Bench-top DNA origami placement is the first demonstration of its kind which facilitates precision placement of single molecules with high efficiency in diffraction-limited sites at a cost of $1/chip. The comprehensive characterization of this technique, and its application as a robust platform for high-throughput biophysics and digital counting of biomarkers through enzyme-free amplification are elucidated here. Furthermore, this technique can serve as a template for the bottom-up fabrication of invaluable biophysical tools such as zero mode waveguides, making them significantly cheaper and more accessible to the scientific community. This platform has the potential to democratize high-throughput single molecule experiments in laboratories worldwide.
ContributorsShetty, Rishabh Manoj (Author) / Hariadi, Rizal F (Thesis advisor) / Gopinath, Ashwin (Committee member) / Varsani, Arvind (Committee member) / Nikkhah, Mehdi (Committee member) / Tillery, Stephen H (Committee member) / Hu, Ye (Committee member) / Arizona State University (Publisher)
Created2019
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Description
ABSTRACT Billions of dollars are spent annually on urine specimen collection and analysis as they are critical clinical components vital to human health. The mid-stream clean catch (MSCC) process is the gold standard of ambulatory urine specimen collection for clinical diagnosis of urinary tract infections (UTI).

ABSTRACT Billions of dollars are spent annually on urine specimen collection and analysis as they are critical clinical components vital to human health. The mid-stream clean catch (MSCC) process is the gold standard of ambulatory urine specimen collection for clinical diagnosis of urinary tract infections (UTI). The MSCC process is over 60 years old and is plagued by ridiculously high specimen contamination rates. The MSCC has resisted numerous attempts aimed at improving it. The purpose of this study was to determine if utilizing the concepts of Human Systems Engineering (HSE) could improve the urine specimen collection process. HSE concepts were not only targeted toward the problems, they were also used in the quest to develop effective solutions. Results obtained demonstrate that HSE concepts, when applied to urine specimen collection, can and do make a difference in terms of specimen quality and patient satisfaction. One low cost easily implemented targeted HSE-informed intervention effort resulted in a specimen contamination rate reduction of 16.6%. A second targeted HSE-informed intervention involving the redesign of the specimen cup, its instruction set, and additional sign placement made it three times less likely for participants to provide a contaminated MSCC sample. The redesigned specimen cup automatically captures and isolates an initial void sample from an MSCC sample, both derived from one continuously provided patient specimen. Clinical utility comes in the form of improved MSCC specimen quality and a separated initial void available for analysis using Nucleic Acid Amplification Testing (NAAT) or other test protocols. Capturing and isolating both an initial void and an MSCC at the same time allows for a more complete diagnostic workup utilizing a higher quality MSCC without requiring the patient to follow two different protocols to urinate into two different specimen cups. The redesigned specimen cup also provides for automatic overflow prevention, incorporates a new ergonomic grip, and a saddle adapter that provides affordances for both women and men in terms of urine capture and the reduced likelihood of urinating on one’s self.
ContributorsWallace, David (Author) / Gutzwiller, Robert S (Thesis advisor) / Branaghan, Russell J (Committee member) / Cooke, Nancy J (Committee member) / Hall, Rick (Committee member) / Arizona State University (Publisher)
Created2021
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Description
In classification applications, such as medical disease diagnosis, the cost of one type of error (false negative) could greatly outweigh the other (false positive) enabling the need of asymmetric error control. Due to this unique nature of the problem, traditional machine learning techniques, even with much improved accuracy, may not

In classification applications, such as medical disease diagnosis, the cost of one type of error (false negative) could greatly outweigh the other (false positive) enabling the need of asymmetric error control. Due to this unique nature of the problem, traditional machine learning techniques, even with much improved accuracy, may not be ideal as they do not provide a way to control the false negatives below a certain threshold. To address this need, a classification algorithm that can provide asymmetric error control is proposed. The theoretical foundation for this algorithm is based on Neyman-Pearson (NP) Lemma and it is complemented with sample splitting and order statistics to pick a threshold that enables an upper bound on the number of false negatives. Additionally, this classifier addresses the imbalance of the data, which is common in medical datasets, by using Hellinger distance as the splitting criterion. This eliminates the need of sampling methods, which add complexity and the need for parameter selection. This approach is used to create a novel tree-based classifier that enables asymmetric error control. Applications, such as prediction of the severity of cardiac arrhythmia, require classification over multiple classes. The NP oracle inequalities for binary classes are not immediately applicable for the multiclass NP classification, leading to a multi-step procedure proposed in this dissertation to extend the algorithm in the context of multiple classes. This classifier is used in predicting various forms of cardiac disease for both binary and multi-class classification problems with not only comparable accuracy metrics but also with full control over the number of false negatives. Moreover, this research allows us to pick the threshold for the classifier in a data adaptive way. This dissertation also shows that this methodology can be extended to non medical applications that require classification with asymmetric error control.
ContributorsBokhari, Wasif (Author) / Bansal, Ajay (Thesis advisor) / Zhang, Yu (Committee member) / Yang, Yezhou (Committee member) / Bahadur, Faisal (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Magnetic resonance imaging (MRI) is a noninvasive imaging modality, which is used for many different applications. The versatility of MRI is in acquiring high resolution anatomical and functional images with no use of ionizing radiation. The contrast in MR images can be engineered by two different mechanisms with imaging parameters

Magnetic resonance imaging (MRI) is a noninvasive imaging modality, which is used for many different applications. The versatility of MRI is in acquiring high resolution anatomical and functional images with no use of ionizing radiation. The contrast in MR images can be engineered by two different mechanisms with imaging parameters (TR, TE, α) and/or contrast agents. The contrast in the former is influenced by the intrinsic properties of the tissue (T1, T2, ρ), while the contrast agents change the relaxation rate of the protons to enhance contrast. Contrast agents have attracted a lot of attention because they can be modified with targeting groups to shed light on some physiological and biological questions, such as the presence of hypoxia in a tissue. Hypoxia, defined as lack of oxygen, has many known ramifications on the outcome of therapy in any condition. Hence its study is very important. The standard gold method to detect hypoxia, immunohistochemical (IHC) staining of pimonidazole, is invasive; however, there are many research groups focused on developing new and mainly noninvasive methods to investigate hypoxia in different tissues.Previously, a novel nitroimidazole-based T1 contrast agent, gadolinium tetraazacyclododecanetetraacetic acid monoamide conjugate of 2-nitroimidazole (GdDO3NI ), has been synthesized and characterized on subcutaneous prostate and lung tumor models. Here, its efficacy and performance on traumatic brain injuries and brain tumors are studied. The pharmacokinetic properties of the contrast agent the perfusion properties of brain tumors are investigated. These results can be used in personalized therapies for more effective results for patients. Gadolinium (Gd), which is a strongly paramagnetic heavy metal, is routinely and widely used as an MR contrast agent by chelation with a biocompatible ligand which is typically cleared through the kidneys. While widely used, there are serious concerns for patients with impaired kidney function, as well as recent studies showed Gd accumulation in the bone and brain. Iron as a physiological ion is also capable of generating contrast in MR images. Here synthesis and characterization of an iron-based hypoxia targeting contrast agent is proposed to eliminate Gd-related complications and provide a cheaper and more economical alternative contrast agent to detect hypoxia.
ContributorsMoghadas, Babak (Author) / Kodibagkar, Vikram D (Thesis advisor) / Beeman, Scott (Committee member) / Muthuswamy, Jitendran (Committee member) / Nikkhah, Mehdi (Committee member) / Turner, Gregory (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Motor skill learning is important to rehabilitation, sports, and many occupations. When attempting to learn or adapt a motor skill, some individuals learn slower or less compared to others despite the same amount of motor practice. This dissertation aims to understand the factors that contributed to such variability in motor

Motor skill learning is important to rehabilitation, sports, and many occupations. When attempting to learn or adapt a motor skill, some individuals learn slower or less compared to others despite the same amount of motor practice. This dissertation aims to understand the factors that contributed to such variability in motor learning, and thereby identify viable methods to enhance motor learning. Behavioral evidence from our lab showed that visuospatial ability is positively related to the extent of motor learning. Neuroimaging studies suggest that motor learning and visuospatial processes share common frontoparietal neural structures, and that this visuospatial-motor relationship may be more pronounced in the right hemisphere compared to the left. Thus, the overall objective of this dissertation is to determine if aspects of motor learning (such as the rate and extent of skill acquisition) may be modifiable through neuromodulation of the right frontoparietal network. In Aim 1, anodal transcranial direct current stimulation (tDCS) was used to test whether modulating the right parietal area affects visuospatial ability and motor skill acquisition. A randomized, three-arm design was used, which added a no-tDCS control group to the double-blinded sham-control protocol to address placebo effects. No tDCS treatment effect was observed, likely due to low statistical power to detect any treatment effects as the study is still ongoing. However, the current results revealed a unique finding that the placebo effect of tDCS was stronger than its treatment effect on motor learning, with implications that tDCS and motor studies should measure and control for placebo effects. In Aim 2, right frontoparietal connectivity during resting-state EEG was estimated via alpha band imaginary coherence to test whether it correlated with visuospatial performance and motor skill acquisition. As a preliminary step towards leveraging the frontoparietal network for EEG-neurofeedback applications, this work found that alpha imaginary coherence was positively correlated with visuospatial function, but not with motor skill acquisition during a limited dose of motor practice (only 5 trials). This work establishes a premise for developing frontoparietal alpha IC-based neurofeedback for cognitive training in rehabilitation, while warranting future studies to test the relationship between alpha IC and motor learning with a more extensive motor training regimen.
ContributorsWang, Peiyuan (Author) / Schaefer, Sydney Y (Thesis advisor) / Buneo, Christopher A (Committee member) / Abbas, James (Committee member) / Lohse, Keith R (Committee member) / Wyckoff, Sarah N (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive technique that offers a unique ability to provide the spatial distribution of relevant biochemical compounds (metabolites). The ‘spectrum’ of information provided by MRSI is used as biomarkers for the differential diagnosis of several diseases such as cancer or neurological disorders. Treatment responsive

Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive technique that offers a unique ability to provide the spatial distribution of relevant biochemical compounds (metabolites). The ‘spectrum’ of information provided by MRSI is used as biomarkers for the differential diagnosis of several diseases such as cancer or neurological disorders. Treatment responsive brain tumors can appear similar to non-responsive tumors on conventional anatomical MR images, earlier in the therapy, leading to a poor prognosis for many patients. Biomarkers such as lactate are particularly of interest in the oncological studies of solid tumors to determine their energy metabolism, blood flow, and hypoxia. Despite the capability of nearly all clinical MRI scanners to perform MRSI only limited integration of MRSI into routine clinical studies has occurred to date. The major challenges affecting its true potential are the inherently long acquisition time, low signal-to-noise (SNR) of the signals, overlapping of spectral lines, or the presence of artifacts. The goal of this dissertation work is to facilitate MRSI in routine clinical studies without affecting the current patient throughput. In this work, the Compressed Sensing (CS) strategy was used to accelerate conventional Point RESolved Spectroscopy (PRESS) MRSI by sampling well below the Shannon-Nyquist limit. Two undersampling strategies, namely the pseudo-random variable density and a novel a priori method was developed and implemented on a clinical scanner. Prospectively undersampled MRSI data was acquired from patients with various brain-related concerns. Spatial-spectral post-processing and CS reconstruction pipeline was developed for multi-channel undersampled data. The fidelity of the CS-MRSI method was determined by comparing the CS reconstructed data to the fully sampled data. Statistical results showed that the a priori approach maintained high spectral fidelity compared to the fully sampled reference for an 80% reduction in scan time. Next, an improvement to the CS-MRSI reconstruction was achieved by incorporating coil sensitivity maps as support in the iterative process. Further, a CS-MRSI-based fast lactate spectroscopic imaging method was developed and implemented to achieve complete water and fat suppression for accurate spatial localization and quantification of lactate in tumors. In vitro phantoms were developed, and the sequence was tested to determine the efficacy of CS-MRSI for low SNR signals, the efficacy of the CS acceleration was determined with statistical analysis.
ContributorsBikkamane Jayadev, Nutandev (Author) / Kodibagkar, Vikram (Thesis advisor) / Chang, John (Committee member) / Robison, Ryan (Committee member) / Smith, Barbara (Committee member) / Sohn, Sung-Min (Committee member) / Arizona State University (Publisher)
Created2021