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ASU Electronic Theses and Dissertations


This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.


In this work, different methods for fabrication of flexible sensors and sensor characterization are studied. Using materials and equipment that is unconventional, it is shown that different processes can be used to create sensors that behave like commercially available sensors. The reason unconventional methods are used is to cut down on cost to produce the sensors as well as enabling the manufacture of custom sensors in different sizes and different configurations. Currently commercially available sensors are expensive and are usually designed for very specific applications. By creating these same types of sensors using new methods and materials, these new sensors …

Contributors
Casanova, Lucas Montgomery, Redkar, Sangram, Rogers, Bradley, et al.
Created Date
2018

Brain Computer Interfaces are becoming the next generation controllers not only in the medical devices for disabled individuals but also in the gaming and entertainment industries. In order to build an effective Brain Computer Interface, which accurately translates the user thoughts into machine commands, it is important to have robust and fail proof signal processing and machine learning modules which operate on the raw EEG signals and estimate the current thought of the user. In this thesis, several techniques used to perform EEG signal pre-processing, feature extraction and signal classification have been discussed, implemented, validated and verified; efficient supervised machine …

Contributors
Manchala, vamsi krishna, Redkar, Sangram, Rogers, Bradley, et al.
Created Date
2015

Human running requires extensive training and conditioning for an individual to maintain high speeds (greater than 10mph) for an extended duration of time. Studies have shown that running at peak speeds generates a high metabolic cost due to the use of large muscle groups in the legs associated with the human gait cycle. Applying supplemental external and internal forces to the human body during the gait cycle has been shown to decrease the metabolic cost for walking, allowing individuals to carry additional weight and walk further distances. Significant research has been conducted to reduce the metabolic cost of walking, however, …

Contributors
Kerestes, Jason, Sugar, Thomas, Redkar, Sangram, et al.
Created Date
2014