Effect of Target Size, Location, and Input Method on Interaction in Immersive Virtual Reality

Although new virtual reality (VR) devices and their contents are actively being released, there are still not enough studies to prepare its interface/interaction standard. In this study, it was investigated whether specific interaction factors influenced task performance and the degree of virtual reality sickness when performing pointing tasks in immersive virtual reality. A smartphone-based VR device was used, and twenty-five targets were placed in a 5 × 5 layout on the VR experimental area that extended to a range similar to the human viewing angle. Task completion time (TCT) was significantly affected by target selection method (p < 0.001) and target size (p < 0.001), whereas the error rate (ER) significantly differed for the target selection method (p < 0.001) and not for the target size (p = 0.057). Target location was observed to be a factor affecting TCT (p < 0.001), but it did not affect the ER (p = 0.876). VR sickness was more severe when the target size was smaller. Gaze selection was found to be more efficient when accuracy is demanded, and manual selection is more efficient for quick selection. Moreover, applying these experimental data to Fitts’ Law showed that the movement time was found to be less affected by the device when using the gaze-selection method. Virtual reality provides a three-dimensional visual environment, but a one-dimensional formula can sufficiently predict the movement time. The result of this study is expected to be a reference for preparing interface/interaction design standards for virtual reality.

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A Test of Fitts' Law in a Dual-Task Paradigm

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/154193129303700909 ◽

1993 ◽

Vol 37 (9) ◽

pp. 559-563

Author(s):

Randa L. Shehab ◽

Robert E. Schlegel

Keyword(s):

Dual Task ◽

Loading Condition ◽

Target Location ◽

Movement Time ◽

Target Size ◽

Movement Amplitude ◽

Fitts Law ◽

Task Loading ◽

Task Conditions ◽

Linear Regressions

A simulated automobile driving environment was used to assess the validity of Fitts' Law under dual-task conditions. An aimed hand movement task was used as the Fitts task representative of reaching for controls on an instrument panel. The task required activation of one of four touch-sensitive response plates upon recognition of an auditory stimulus. Movement difficulty was manipulated by varying target location and size. Target location was examined at four levels corresponding to position in a 2 × 2 array. Distances of the targets from the two-o'clock position on the steering wheel ranged from 27 cm to 53 cm. The target plates were square and measured 1.27 cm (1/2 inch) or 0.64 cm (1/4 inch) along the side. The eight combinations of movement amplitude and target size yielded seven unique levels of Fitts' Index of Difficulty (ID) ranging from 5.4 to 7.4. The movement task was performed alone and in combination with two other tasks to create three levels of task loading. A display monitoring task was used to represent the visual demands of driving while an unstable tracking task was used to represent the perceptual-motor demands of driving. Following adequate training, ten subjects performed three replications of six task conditions (three loading levels x two target sizes). Within each replication, the order of testing was counterbalanced across subjects. The dual-task visual loading condition involving the movement and monitoring tasks consistently resulted in the longest reaction times. The dual-task perceptual-motor loading condition involving the movement and tracking tasks resulted in consistently longer movement times. Fitts' ID had a significant effect on both reaction time and movement time for all three conditions of task loading. However, separate linear regressions of movement time on ID for each task loading level resulted in R2 values of 0.66 to 0.82. Multiple linear regressions involving target size and movement amplitude as predictor variables provided better predictions with R2 values of 0.90 to 0.93. The regression equations provided in this paper may be used by designers to estimate differences in response time due to control size and location.

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An Immersive Virtual Reality Therapy Application for Iraq War Veterans with PTSD: From Training to Toy to Treatment

PsycEXTRA Dataset ◽

10.1037/e463912006-001 ◽

2004 ◽

Author(s):

A. A. Rizzo ◽

◽

J. Pair ◽

P. J. McNerney ◽

E. Eastlund ◽

...

Keyword(s):

Virtual Reality ◽

Iraq War ◽

Reality Therapy ◽

Immersive Virtual Reality ◽

War Veterans ◽

Virtual Reality Therapy

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Immersive virtual reality effects on balance

Frontiers in Neuroengineering ◽

10.3389/conf.neuro.14.2009.06.066 ◽

2009 ◽

Vol 2 ◽

Author(s):

Mauro A.

Keyword(s):

Virtual Reality ◽

Immersive Virtual Reality

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Spatial suppression due to statistical regularities is driven by distractor suppression not by target activation

10.31234/osf.io/zbcjv ◽

2018 ◽

Author(s):

Michel Failing ◽

Benchi Wang ◽

Jan Theeuwes

Keyword(s):

High Probability ◽

Target Location ◽

Target Selection ◽

Visual Space ◽

Alternative Interpretation ◽

Distractor Location ◽

Target Presentation ◽

Statistical Regularities ◽

Low Probability ◽

Presentation Experiment

Where and what we attend to is not only determined by what we are currently looking for but also by what we have encountered in the past. Recent studies suggest that biasing the probability by which distractors appear at locations in visual space may lead to attentional suppression of high probability distractor locations which effectively reduces capture by a distractor but also impairs target selection at this location. However, in many of these studies introducing a high probability distractor location was tantamount to increasing the probability of the target appearing in any of the other locations (i.e. the low probability distractor locations). Here, we investigate an alternative interpretation of previous findings according to which attentional selection at high probability distractor locations is not suppressed. Instead, selection at low probability distractor locations is facilitated. In two visual search tasks, we found no evidence for this hypothesis: neither when there was only a bias in target presentation but no bias in distractor presentation (Experiment 1), nor when there was only a bias in distractor presentation but no bias in target presentation (Experiment 2). We conclude that recurrent presentation of a distractor in a specific location leads to attentional suppression of that location through a mechanism that is unaffected by any regularities regarding the target location.

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