Abstract
Background The motor learning literature focuses on relatively simple laboratory-tasks due to their highly controlled manner and the ease to apply different manipulations to induce learning and adaptation. In recent work we introduced a billiards paradigm and demonstrated the feasibility of real-world neuroscience using wearables for naturalistic full-body motion tracking and mobile brain imaging. Here we developed an embodied virtual reality (VR) environment to our real-world billiards paradigm, which allows us to control the visual feedback for this complex real-world task, while maintaining the sense of embodiment.
Methods The setup was validated by comparing real-world ball trajectories with the embodied VR trajectories, calculated by the physics engine. We then ran our real-world learning protocol in the embodied VR. 10 healthy human subjects played repeated trials of the same billiard shot when they held the physical cue and hit a physical ball on the table while seeing it all in VR.
Results We found comparable learning trends in the embodied VR to those we previously reported in the real-world task.
Conclusions Embodied VR can be used for learning real-world tasks in a highly controlled VR environment which enables applying visual manipulations, common in laboratory-tasks and in rehabilitation, to a real-world full-body task. Such a setup can be used for rehabilitation, where the use of VR is gaining popularity but the transfer to the real-world is currently limited, presumably, due to the lack of embodiment. The embodied VR enables to manipulate feedback and apply perturbations to isolate and assess interactions between specific motor learning components mechanisms, thus enabling addressing the current questions of motor-learning in real-world tasks.
Abbreviations
- EVR
- Embodied virtual reality;
- DoF
- Degrees of freedom;
- MoCap
- Motion capture;
- SoE
- Sense of Embodiment;
- IMU
- inertial measurement unit;
- HMD
- head-mounted display;
- RMSE
- root mean squared error;
- GV
- generalized variance;
- PCA
- Principal component analysis;
- VPE
- Velocity profile error;