Responses to a Virtual Reality Grocery Store in Persons with and without Vestibular Dysfunction

2006 ◽  
Vol 9 (2) ◽  
pp. 152-156 ◽  
Author(s):  
Susan L. Whitney ◽  
Patrick J. Sparto ◽  
Larry F. Hodges ◽  
Sabarish V. Babu ◽  
Joseph M. Furman ◽  
...  
2008 ◽  
Vol 7 (2) ◽  
Author(s):  
T.D. Parsons ◽  
A.A. Rizzo ◽  
J. Brennan ◽  
T.M. Silva ◽  
E.M. Zelinski

Author(s):  
James Cunningham ◽  
Christian Lopez ◽  
Omar Ashour ◽  
Conrad S. Tucker

Abstract In this work, a Deep Reinforcement Learning (RL) approach is proposed for Procedural Content Generation (PCG) that seeks to automate the generation of multiple related virtual reality (VR) environments for enhanced personalized learning. This allows for the user to be exposed to multiple virtual scenarios that demonstrate a consistent theme, which is especially valuable in an educational context. RL approaches to PCG offer the advantage of not requiring training data, as opposed to other PCG approaches that employ supervised learning approaches. This work advances the state of the art in RL-based PCG by demonstrating the ability to generate a diversity of contexts in order to teach the same underlying concept. A case study is presented that demonstrates the feasibility of the proposed RL-based PCG method using examples of probability distributions in both manufacturing facility and grocery store virtual environments. The method demonstrated in this paper has the potential to enable the automatic generation of a variety of virtual environments that are connected by a common concept or theme.


2015 ◽  
Vol 180 (3S) ◽  
pp. 143-149 ◽  
Author(s):  
Pinata H. Sessoms ◽  
Kim R. Gottshall ◽  
John-David Collins ◽  
Amanda E. Markham ◽  
Kathrine A. Service ◽  
...  

2011 ◽  
Vol 145 (2_suppl) ◽  
pp. P158-P159
Author(s):  
Pa-Chun Wang ◽  
Chia-Huang Chang ◽  
Mu-Chun Su ◽  
Shih-Ching Yeh ◽  
Te-Yung Fang

2020 ◽  
Vol 26 ◽  
Author(s):  
Tomasz Stankiewicz ◽  
Mariusz Gujski ◽  
Artur Niedzielski ◽  
Lechosław P. Chmielik

2012 ◽  
Vol 22 (5,6) ◽  
pp. 273-281 ◽  
Author(s):  
M. Pavlou ◽  
R.G. Kanegaonkar ◽  
D. Swapp ◽  
D.E. Bamiou ◽  
M. Slater ◽  
...  

2021 ◽  
Vol 36 (6) ◽  
pp. 1052-1052
Author(s):  
Danielle R Hardesty ◽  
Carmen Chek ◽  
Michael Persin ◽  
Emma Barr ◽  
Hannah Sasser ◽  
...  

Abstract Background/Problem Neuropsychologists are often asked to evaluate patients’ functional capacities, yet traditional neuropsychological tests have limited correspondence with real-world outcomes. The Virtual Environment Grocery store (VEGS) is a virtual environment that stimulates shopping tasks. Previous research has found support for the construct validity of the VEGS among older adults (Parsons & Barnett, 2017); however, no extant research has examined relationships between the VEGS and adaptive functioning among older adults. Method Older adults (n = 30; age 43–90 M = 77.09, SD = 12.94) were administered the Virtual Reality Grocery Store (VEGS) and the Texas Functional Living Scale (TFLS) and completed the Instruments of Daily Activities (IADLS) Questionnaire. Results VEGS variables explained 39.6% of the variance in self-reported adaptive functioning (I, e., the IADLS) and 60.0% of the variance in performance-based adaptive functioning (i.e., the TFLS). Conclusion These results suggest that the VEGS is a predictor of adaptive functioning – particularly when measured with a performance-based measure – among older adults.


2014 ◽  
Vol 22 (6) ◽  
pp. 915-921 ◽  
Author(s):  
Shih-Ching Yeh ◽  
Shuya Chen ◽  
Pa-Chun Wang ◽  
Mu-Chun Su ◽  
Chia-Huang Chang ◽  
...  

2021 ◽  
Vol 121 (9) ◽  
pp. A64
Author(s):  
J. Pilut ◽  
R. Litchfield ◽  
J. Hollis ◽  
L. Lanningham-Foster ◽  
M. Wolff

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