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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.


Gait and balance disorders are the second leading cause of falls in the elderly. Investigating the changes in static and dynamic balance due to aging may provide a better understanding of the effects of aging on postural control system. Static and dynamic balance were evaluated in a total of 21 young (21-35 years) and 22 elderly (50-75 years) healthy subjects while they performed three different tasks: quiet standing, dynamic weight shifts, and over ground walking. During the quiet standing task, the subjects stood with their eyes open and eyes closed. When performing dynamic weight shifts task, subjects shifted their Center …

Contributors
Balasubramanian, Shruthi, Krishnamurthi, Narayanan, Abbas, James, et al.
Created Date
2014

Injuries and death associated with fall incidences pose a significant burden to society, both in terms of human suffering and economic losses. The main aim of this dissertation is to study approaches that can reduce the risk of falls. One major subset of falls is falls due to neurodegenerative disorders such as Parkinson’s disease (PD). Freezing of gait (FOG) is a major cause of falls in this population. Therefore, a new FOG detection method using wavelet transform technique employing optimal sampling window size, update time, and sensor placements for identification of FOG events is created and validated in this dissertation. …

Contributors
Rezvanian, Saba, Lockhart, Thurmon, Buneo, Christopher, et al.
Created Date
2019