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Virtual Exertions: a user interface combining visual information, kinesthetics and biofeedback for virtual object

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    This study introduces a novel system for natural interaction in virtual reality (VR) using muscle exertion classification. Users can grasp and move virtual objects intuitively by combining visual, kinesthetic, and electromyogram (EMG) biofeedback.

    Keywords:
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    Area of Science:

    • Human-Computer Interaction
    • Virtual Reality
    • Biofeedback Systems

    Background:

    • Current virtual reality (VR) interactions often lack naturalness, deviating from real-world object manipulation methods.
    • Existing interfaces struggle to provide intuitive control over virtual objects, hindering user immersion and experience.

    Purpose of the Study:

    • To develop and demonstrate a VR interaction system that utilizes natural body movements.
    • To enable users to interact with virtual objects using muscle exertion and biofeedback.

    Main Methods:

    • Combining visual information, kinesthetics, and electromyograms (EMG) for user input.
    • Classifying muscle exertion based on simulated physical world masses to control virtual objects.
    • Implementing a system for grasping, moving, and dropping virtual objects through calibrated muscle exertion.

    Main Results:

    • Users can consistently reproduce calibrated muscle exertions for controlling virtual objects.
    • The system allows for a more natural and intuitive interface with virtual environments.
    • Demonstrated a novel method for interfacing with virtual objects through biofeedback and kinesthetics.

    Conclusions:

    • The developed system enhances natural interaction in virtual reality by integrating multiple sensory inputs.
    • Muscle exertion classification based on physical properties offers a promising approach for intuitive VR object manipulation.
    • This technology opens new possibilities for immersive and realistic user experiences in virtual environments.