MovementVR: An open-source tool for the study of motor control and learning in virtual reality

Area of Science:

• Neuroscience
• Computer Science
• Rehabilitation Science

Background:

• Virtual reality (VR) enhances ecological validity in motor control research through immersive environments and precise motion tracking.
• Designing complex VR motor tasks requires advanced programming, limiting accessibility for researchers and clinicians.
• Existing platforms often necessitate coding expertise, creating barriers to entry.

Purpose of the Study:

• To introduce MovementVR, an open-source platform for creating customizable, naturalistic VR reaching tasks.
• To eliminate the need for coding expertise in designing VR motor experiments.
• To enhance the accessibility and affordability of VR for motor control and learning research.

Main Methods:

• Developed an open-source platform, MovementVR, featuring a graphical user interface (GUI).
• Integrated physics-based hand-object interactions and real-time hand tracking.
• Supported flexible experimental paradigms, including motor adaptation and reinforcement learning.

Main Results:

• MovementVR enables the creation of realistic VR reaching tasks without programming.
• The platform offers extensive customization while preserving ecological validity.
• Compatibility with consumer-grade VR headsets reduces financial barriers.

Conclusions:

• MovementVR significantly lowers technical and financial barriers for VR-based motor research and rehabilitation.
• The platform facilitates broader adoption of immersive technologies in studying movement.
• MovementVR empowers researchers and clinicians to design and implement complex VR tasks more efficiently.