In this work, we investigate the influence of different visualizations on a manipulation task in virtual reality (VR). Without the haptic feedback of the real world, grasping in VR might result in intersections with virtual objects. As people are highly sensitive when it comes to perceiving collisions, it might look more appealing to avoid intersections and visualize non-colliding hand motions. However, correcting the position of the hand or fingers results in a visual-proprioceptive discrepancy and must be used with caution. Furthermore, the lack of haptic feedback in the virtual world might result in slower actions as a user might not know exactly when a grasp has occurred. This reduced performance could be remediated with adequate visual feedback.
In this study, we analyze the performance, level of ownership, and user preference of eight different visual feedback techniques for virtual grasping. Three techniques show the tracked hand (with or without grasping feedback), even if it intersects with the grasped object. Another three techniques display a hand without intersections with the object, called outer hand, simulating the look of a real world interaction. One visualization is a compromise between the two groups, showing both a primary outer hand and a secondary tracked hand. Finally, in the last visualization the hand disappears during the grasping activity.
In an experiment, users perform a pick-and-place task for each feedback technique. We use high fidelity marker-based hand tracking to control the virtual hands in real time. We found that the tracked hand visualizations result in better performance, however, the outer hand visualizations were preferred. We also find indications that ownership is higher with the outer hand visualizations.
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Effects of Sensory Feedback and Collider Size on Reach-to-Grasp Coordination in Haptic-Free Virtual Reality
Technological advancements and increased access have prompted the adoption of head- mounted display based virtual reality (VR) for neuroscientific research, manual skill training, and neurological rehabilitation. Applications that focus on manual interaction within the virtual environment (VE), especially haptic-free VR, critically depend on virtual hand-object collision detection. Knowledge about how multisensory integration related to hand-object collisions affects perception-action dynamics and reach-to-grasp coordination is needed to enhance the immersiveness of interactive VR. Here, we explored whether and to what extent sensory substitution for haptic feedback of hand-object collision (visual, audio, or audiovisual) and collider size (size of spherical pointers representing the fingertips) influences reach-to-grasp kinematics. In Study 1, visual, auditory, or combined feedback were compared as sensory substitutes to indicate the successful grasp of a virtual object during reach-to-grasp actions. In Study 2, participants reached to grasp virtual objects using spherical colliders of different diameters to test if virtual collider size impacts reach-to-grasp. Our data indicate that collider size but not sensory feedback modality significantly affected the kinematics of grasping. Larger colliders led to a smaller size-normalized peak aperture. We discuss this finding in the context of a possible influence of spherical collider size on the perception of the virtual object’s size and hence effects on motor planning of reach-to-grasp. Critically, reach-to-grasp spatiotemporal coordination patterns were robust to manipulations of sensory feedback modality and spherical collider size, suggesting that the nervous system adjusted the reach (transport) component commensurately to the changes in the grasp (aperture) component. These results have important implications for research, commercial, industrial, and clinical applications of VR.
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- NSF-PAR ID:
- 10301217
- Date Published:
- Journal Name:
- Frontiers in Virtual Reality
- Volume:
- 2
- ISSN:
- 2673-4192
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Control of reach-to-grasp movements for deft and robust interactions with objects requires rapid sensorimotor updating that enables online adjustments to changing external goals (e.g., perturbations or instability of objects we interact with). Rarely do we appreciate the remarkable coordination in reach-to-grasp, until control becomes impaired by neurological injuries such as stroke, neurodegenerative diseases, or even aging. Modeling online control of human reach-to-grasp movements is a challenging problem but fundamental to several domains, including behavioral and computational neuroscience, neurorehabilitation, neural prostheses, and robotics. Currently, there are no publicly available datasets that include online adjustment of reach-to-grasp movements to object perturbations. This work aims to advance modeling efforts of reach-to-grasp movements by making publicly available a large kinematic and EMG dataset of online adjustment of reach-to-grasp movements to instantaneous perturbations of object size and distance performed in immersive haptic-free virtual environment (hf-VE). The presented dataset is composed of a large number of perturbation types (10 for both object size and distance) applied at three different latencies after the start of the movement.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/frvir.2021.648529
