Effects of Multisensory Feedback on the Perception and Performance of Virtual Reality Hand-Retargeted Interaction
<|reference_start|>Effects of Multisensory Feedback on the Perception and Performance of Virtual Reality Hand-Retargeted Interaction: Retargeting methods that modify the visual representation of real movements have been widely used to expand the interaction space and create engaging virtual reality experiences. For optimal user experience and performance, it is essential to specify the perception of retargeting and utilize the appropriate range of modification parameters. However, previous studies mostly concentrated on whether users perceived the target sense or not and rarely examined the perceptual accuracy and sensitivity to retargeting. Moreover, it is unknown how the perception and performance in hand-retargeted interactions are influenced by multisensory feedback. In this study, we used rigorous psychophysical methods to specify users' perceptual accuracy and sensitivity to hand-retargeting and provide acceptable ranges of retargeting parameters. We also presented different multisensory feedback simultaneously with the retargeting to probe its effect on users' perception and task performance. The experimental results showed that providing continuous multisensory feedback, proportionate to the distance between the virtual hand and the targeted destination, heightened the accuracy of users' perception of hand retargeting without altering their perceptual sensitivity. Furthermore, the utilization of multisensory feedback considerably improved the precision of task performance, particularly at lower gain factors. Based on these findings, we propose design guidelines and potential applications of VR hand-retargeted interactions and multisensory feedback for optimal user experience and performance.<|reference_end|>
@article{jang2024effects,
    title={Effects of Multisensory Feedback on the Perception and Performance of
  Virtual Reality Hand-Retargeted Interaction},
    author={Hyunyoung Jang, Jinwook Kim, Jeongmi Lee},
    journal={IEEE Access, 2024},
    year={2024},
    doi={10.1109/ACCESS.2024.3450512},
    archivePrefix={arXiv},
    eprint={2404.03899},
    primaryClass={cs.HC}
}