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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.


There has been tremendous technological advancement in the past two decades. Faster computers and improved sensing devices have broadened the research scope in computer vision. With these developments, the task of assessing the quality of human actions, is considered an important problem that needs to be tackled. Movement quality assessment finds wide range of application in motor control, health-care, rehabilitation and physical therapy. Home-based interactive physical therapy requires the ability to monitor, inform and assess the quality of everyday movements. Obtaining labeled data from trained therapists/experts is the main limitation, since it is both expensive and time consuming. Motivated by …

Contributors
Som, Anirudh, Turaga, Pavan, Krishnamurthi, Narayanan, et al.
Created Date
2016

Many studies on human walking pattern assume that adult gait is characterized by bilateral symmetrical behavior. It is well understood that maintaining symmetry in walking patterns increases energetic eciency. We present a framework to provide a quantitative assessment of human walking patterns, especially assessments related to symmetric and asymmetric gait patterns purely based on glide reflection. A Gliding symmetry score is calculated from the data obtained from Motion Capture(MoCap) system. Six primary joints (Shoulder, Elbow, Palm, Hip, Knee, Foot) are considered for this study. Two dierent abnormalities were chosen and studied carefully. All the two gaits were mimicked in controlled …

Contributors
Potaraju, Chaitanya Prakash, Turaga, Pavan Kumar, Krishnamurthi, Narayanan, et al.
Created Date
2017