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 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.
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.
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Details
Title
- Spatial-temporal characteristics of multisensory integration
Contributors
- Sim, Sung Hun (Author)
- Wu, Bing (Thesis advisor)
- Cooke, Nancy J. (Committee member)
- Gray, Robert (Committee member)
- Branaghan, Russell (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2017
Subjects
Resource Type
Collections this item is in
Note
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thesisPartial requirement for: Ph. D., Arizona State University, 2017
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bibliographyIncludes bibliographical references (pages 92-102)
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Field of study: Human systems engineering
Citation and reuse
Statement of Responsibility
by Sung Hun Sim