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- All Subjects: TDCS
- All Subjects: Three-dimensional printing
- Genre: Academic theses
- Creators: Abbas, James
Description
Transcranial electrical stimulation (tES) is a non-invasive brain stimulation therapy that has shown potential in improving motor, physiological and cognitive functions in healthy and diseased population. Typical tES procedures involve application of weak current (< 2 mA) to the brain via a pair of large electrodes placed on the scalp. While the therapeutic benefits of tES are promising, the efficacy of tES treatments is limited by the knowledge of how current travels in the brain. It has been assumed that the current density and electric fields are the largest, and thus have the most effect, in brain structures nearby the electrodes. Recent studies using finite element modeling (FEM) have suggested that current patterns in the brain are diffuse and not concentrated in any particular brain structure. Although current flow modeling is useful means of informing tES target optimization, few studies have validated tES FEM models against experimental measurements. MREIT-CDI can be used to recover magnetic flux density caused by current flow in a conducting object. This dissertation reports the first comparisons between experimental data from in-vivo human MREIT-CDI during tES and results from tES FEM using head models derived from the same subjects. First, tES FEM pipelines were verified by confirming FEM predictions agreed with analytic results at the mesh sizes used and that a sufficiently large head extent was modeled to approximate results on human subjects. Second, models were used to predict magnetic flux density, and predicted and MREIT-CDI results were compared to validate and refine modeling outcomes. Finally, models were used to investigate inter-subject variability and biological side effects reported by tES subjects. The study demonstrated good agreements in patterns between magnetic flux distributions from experimental and simulation data. However, the discrepancy in scales between simulation and experimental data suggested that tissue conductivities typically used in tES FEM might be incorrect, and thus performing in-vivo conductivity measurements in humans is desirable. Overall, in-vivo MREIT-CDI in human heads has been established as a validation tool for tES predictions and to study the underlying mechanisms of tES therapies.
ContributorsIndahlastari, Aprinda (Author) / Sadleir, Rosalind J (Thesis advisor) / Abbas, James (Committee member) / Frakes, David (Committee member) / Kleim, Jeffrey (Committee member) / Kodibagkar, Vikram (Committee member) / Arizona State University (Publisher)
Created2017
Description
With the growing popularity of 3d printing in recreational, research, and commercial enterprises new techniques and processes are being developed to improve the quality of parts created. Even so, the anisotropic properties is still a major hindrance of parts manufactured in this method. The goal is to produce parts that mimic the strength characteristics of a comparable part of the same design and materials created using injection molding. In achieving this goal the production cost can be reduced by eliminating the initial investment needed for the creation of expensive tooling. This initial investment reduction will allow for a wider variant of products in smaller batch runs to be made available. This thesis implements the use of ultraviolet (UV) illumination for an in-process laser local pre-deposition heating (LLPH). By comparing samples with and without the LLPH process it is determined that applied energy that is absorbed by the polymer is converted to an increase in the interlayer temperature, and resulting in an observed increase in tensile strength over the baseline test samples. The increase in interlayer bonding thus can be considered the dominating factor over polymer degradation.
ContributorsKusel, Scott Daniel (Author) / Hsu, Keng (Thesis advisor) / Sodemann, Angela (Committee member) / Kannan, Arunachala M (Committee member) / Arizona State University (Publisher)
Created2017
Description
The American Diabetes Association reports that diabetes costs $322 billion annually and affects 29.1 million Americans. The high out-of-pocket cost of managing diabetes can lead to noncompliance causing serious and expensive complications. There is a large market potential for a more cost-effective alternative to the current market standard of screen-printed self-monitoring blood glucose (SMBG) strips. Additive manufacturing, specifically 3D printing, is a developing field that is growing in popularity and functionality. 3D printers are now being used in a variety of applications from consumer goods to medical devices. Healthcare delivery will change as the availability of 3D printers expands into patient homes, which will create alternative and more cost-effective methods of monitoring and managing diseases, such as diabetes. 3D printing technology could transform this expensive industry. A 3D printed sensor was designed to have similar dimensions and features to the SMBG strips to comply with current manufacturing standards. To make the sensor electrically active, various conductive filaments were tested and the conductive graphene filament was determined to be the best material for the sensor. Experiments were conducted to determine the optimal print settings for printing this filament onto a mylar substrate, the industry standard. The reagents used include a mixture of a ferricyanide redox mediator and flavin adenine dinucleotide dependent glucose dehydrogenase. With these materials, each sensor only costs $0.40 to print and use. Before testing the 3D printed sensor, a suitable design, voltage range, and redox probe concentration were determined. Experiments demonstrated that this novel 3D printed sensor can accurately correlate current output to glucose concentration. It was verified that the sensor can accurately detect glucose levels from 25 mg/dL to 400 mg/dL, with an R2 correlation value as high as 0.97, which was critical as it covered hypoglycemic to hyperglycemic levels. This demonstrated that a 3D-printed sensor was created that had characteristics that are suitable for clinical use. This will allow diabetics to print their own test strips at home at a much lower cost compared to SMBG strips, which will reduce noncompliance due to the high cost of testing. In the future, this technology could be applied to additional biomarkers to measure and monitor other diseases.
ContributorsAdams, Anngela (Author) / LaBelle, Jeffrey (Thesis advisor) / Pizziconi, Vincent (Committee member) / Abbas, James (Committee member) / Arizona State University (Publisher)
Created2017
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 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