ETDs

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.

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Spatial-temporal characteristics of multisensory integration

Description
We experience spatial separation and temporal asynchrony between visual and

haptic information in many virtual-reality, augmented-reality, or teleoperation systems.

Three studies were conducted to examine the spatial and temporal characteristic of

multisensory integration. Participants interacted with virtual springs using both visual and

haptic senses, and their perception of stiffness and ability to differentiate stiffness…

We experience spatial separation and temporal asynchrony between visual and

haptic information in many virtual-reality, augmented-reality, or teleoperation systems.

Three studies were conducted to examine the spatial and temporal characteristic of

multisensory integration. Participants interacted with virtual springs using both visual and

haptic senses, and their perception of stiffness and ability to differentiate stiffness were

measured. The results revealed that a constant visual delay increased the perceived stiffness,

while a variable visual delay made participants depend more on the haptic sensations in

stiffness perception. We also found that participants judged stiffness stiffer when they

interact with virtual springs at faster speeds, and interaction speed was positively correlated

with stiffness overestimation. In addition, it has been found that participants could learn an

association between visual and haptic inputs despite the fact that they were spatially

separated, resulting in the improvement of typing performance. These results show the

limitations of Maximum-Likelihood Estimation model, suggesting that a Bayesian

inference model should be used.
ContributorsSim, Sung Hun (Author) / Wu, Bing (Thesis advisor) / Cooke, Nancy J. (Committee member) / Gray, Robert (Committee member) / Branaghan, Russell (Committee member) / Arizona State University (Publisher)
Created2017