Provision of the perception of pseudo-weight through tracking offsets in virtual reality (VR) allows users to estimate the weight of virtual objects. However, the contribution of the user's real-time perception to such illusions is unknown. Here, we focus on this issue using a brain-computer interface (BCI), through which the user's perception of the weight of virtual objects can be detected in real-time and used to adjust the tracking offset in a closed loop. We first trained a computational model with electroencephalography (EEG) data by asking users to imagine lifting a heavy or a light ball. With this model, the user's perception of the object weight could be detected through the BCI in real-time to adjust the tracking offset, thereby enabling further generation of a more realistic visual sensation. Then, we evaluated the effects of the BCI tracking offset on the perception of the weights of three virtual objects used to simulate real objects, namely, tennis, billiard, and bowling balls. Our results showed that the BCI tracking offset could assist participants in generating perceived weights for virtual objects in VR. We further showed that our approach can provide weight perception through real-time adjustment of the tracking offset, which might be useful for new virtual objects that appear suddenly in the virtual environment. Additionally, most participants (78%) preferred this BCI tracking offset system for weight perception. This article provides the first quantification of weight perception for a virtual object with a BCI that can be used to adjust the tracking offset in real-time for pseudo-weight perception in VR.

Physical practice with one hand results in performance gains of the other (un-practiced) hand in a unilateral motor task. Yet how it induces performance gains of interlimb coordination in the bimanual movements between trained limb and the opposite, untrained limb is unclear. The present study designed a game-like interactive system for physical practice, in which an avatar’s hands could be controlled itself or by the subject during a bimanual movement task in an immersive virtual reality environment. Participants practiced with the bimanual task by simultaneously drawing non-symmetric three-sided squares (e.g., U and C) to learn limb coordination with the following training strategies: (1) performing and seeing a bimanual task (BH-BH); (2) performing a unimanual task with right hand and seeing a bimanual action (RH-BH); (3) not performing a task but seeing a bimanual action (noH-BH); (4) performing and seeing a unimanual task (RH-RH). We found that the learning performance was better after BH-BH and RH-BH compared with other training strategies. In addition, we examined the effects of virtual hand representations on the learning performance after RH-BH. We found that the performance after training was increased with the realism level of virtual hands. These findings suggest that the proposed approach of RH-BH with realistic virtual hand would result in transfer of coordination skill to the unpracticed hand, which puts forward a new approach for learning and rehabilitation of coordination skill in patients with unilateral motor deficit in immersive environments.