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Andrea H. Mason
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Journal Articles
Publisher: Journals Gateway
PRESENCE: Virtual and Augmented Reality (2023) 32: 129–146.
Published: 01 December 2023
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Virtual reality (VR) has potential benefits for training and rehabilitation (Lei et al., 2019 ; Rutkowski et al., 2020 ). In some instances, understanding how performance in VR relates to performance in the real world is a necessary step in building effective environments. This study was designed to determine whether gait in VR changes over time (adaptation), and whether it approaches natural environment performance over time (habituation). Nineteen young adults walked over a gait mat in a real hallway for five minutes and a virtual hallway for three 10-minute blocks. Results indicated that gait was significantly different in the natural environment compared to the first five minutes of immersion (p < 0.05). Group averages also demonstrated that after 10–15 minutes of immersion, there was no statistical difference between the virtual and natural environments across any of the gait measures (p > 0.05). However, individual differences in gait behavior were also evident. While some participants matched performance between virtual and natural environments by the end of the 30-minute session, others did not. These findings provide evidence that individuals adapt differently to motor tasks in VR and suggest that when gait is required in VR, the environment may need to be tailored to the individual to achieve desired outcomes.
Journal Articles
Publisher: Journals Gateway
Presence: Teleoperators and Virtual Environments (2011) 20 (6): 577–590.
Published: 01 December 2011
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The modeling of human movement is vital for a complete understanding of complex human–computer interaction. As three-dimensional collaborative tangible user interfaces (TUIs) evolve, research is needed to understand how people physically interact with each other within a virtual environment. Previous study of physical collaboration in virtual environments has utilized Fitts' law to model gross upper-extremity movement in a passing task. However, no study has modeled passing tasks that require precision grasp with the human hand, an important feature of human–computer interaction in TUIs. The purpose of this study was to evaluate the validity of Fitts' law in modeling movement time for a precision passing task in a 3D TUI, and to assess the coordination between passer and receiver using kinematic parameters. In this experiment, 12 participants (six male, mean age 22.6 years) performed a prehensile passing task within a desktop virtual environment. Results detail the kinematic events required to achieve the necessary temporal and spatial coordination specific to the passing task. Further, results indicate that Fitts' model does not adequately explain movement time for this task ( R 2 = .51). This finding challenges the external validity of previous results. We argue that the task-specific complexity of human neuromotor control should be considered when using predictive models in 3D TUI design.
Journal Articles
Publisher: Journals Gateway
Presence: Teleoperators and Virtual Environments (2004) 13 (5): 507–519.
Published: 01 October 2004
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This work explored how the presence of graphical information about self-movement affected reach-to-grasp movements in an augmented environment. Twelve subjects reached to grasp objects that were passed by a partner or rested on a table surface. Graphical feedback about self-movement was available for half the trials and was removed for the other half. Results indicated that removing visual feedback about self-movement in an object-passing task dramatically affected both the receiver's movement to grasp the object and the time to transfer the object between partners. Specifically, the receiver's deceleration time, and temporal and spatial aspects of grasp formation, showed significant effects. Results also indicated that the presence of a graphic representation of self-movement had similar effects on the kinematics of reaching to grasp a stationary object on a table as for one held by a stationary or moving partner. These results suggest that performance of goal-directed movements, whether to a stationary object on a table surface or to objects being passed by a stationary or moving partner, benefits from a crude graphical representation of the finger pads. The role of providing graphic feedback about self-movement is discussed for tasks requiring precision. Implications for the use of kinematic measures in the field of Human-Computer Interaction (HCI) are also discussed.