In virtual environments, users can embody diverse avatars beyond physical constraints. The avatar-induced cognitive transformation (i.e. Proteus effect) can contribute to engineer self-perception, promote empathy and augment human capabilities. However, when the physicality of the avatar differs greatly from that of the user, the discrepancy between bodily sensation and prediction will inhibit embodiment. Therefore, it's challenging to evoke a high sense of embodiment in avatars that have different body structures or textures based on visual feedback alone. We propose a method to modulate movement impedance (inertia, viscosity, stiffness) of our own body in response to embodied avatars using a wearable haptic device, enhancing the sense of body ownership and the plausibility of interaction using that new avatar. Using Bayesian optimization, we identified individually optimized haptic parameters that maximize subjective plausibility for each user. Our results revealed that Bayesian optimization significantly enhanced users' perceived plausibility of the avatar via haptic feedback. The optimal parameters exhibited substantial inter-individual variation, highlighting the importance of characterizing user-specific motor sensations. On the other hand, regression analysis found no clear correlation between avatar impression ratings and optimal haptic parameters, suggesting subjective plausibility formation involves personal interpretations beyond measurable impressions.

We propose Selfrionette, a controller that uses fingertip force input to drive avatar movements in virtual reality (VR). This system enables users to interact with virtual objects and walk in VR using only fingertip force, overcoming physical and spatial constraints. Additionally, by fixing users’ fingers, it provides users with counterforces equivalent to the applied force, allowing for diverse and wide dynamic range haptic feedback by adjusting the relationship between force input and virtual movement. To evaluate the effectiveness of the proposed method, this paper focuses on hand interaction as a first step. In User Study 1, we measured usability and embodiment during reaching tasks under Selfrionette, body tracking, and finger tracking conditions. In User Study 2, we investigated whether users could perceive haptic properties such as weight, friction, and compliance under the same conditions as User Study 1. Selfrionette was found to be comparable to body tracking in realism of haptic interaction, enabling embodied avatar experiences even in limited spatial conditions.

Humans can estimate the properties of wielded objects (e.g., inertia and viscosity) using the force applied to the hand. We focused on this mechanism and aimed to represent the properties of wielded objects by dynamically changing the force applied to the hand. We propose MetamorphX, which uses control moment gyroscopes (CMGs) to generate ungrounded, 3-degrees of freedom moment feedback. The high-response moments obtained CMGs allow the inertia and viscosity of motion to be set to the desired values via impedance control. A technical evaluation indicated that our device can generate a moment with a 60-ms delay. The inertia and viscosity of motion were varied by 0.01 kgm2 and 0.1 Ns, respectively. Additionally, we demonstrated that our device can dynamically change the inertia and viscosity of motion through virtual reality applications.

Several virtual reality (VR) proxies have been developed that can emulate impact sensations by generating actual forces on the hand. Although these proxies contribute to increasing the reality of VR, they still have some limitations, such as high latency, high power consumption, and low frequency to provide impact sensations. To overcome these limitations, we first propose a method to provide an impact sensation without actual force generation by quickly changing the rotational inertia of a handheld proxy while users are swinging it. Then, we developed Unident, a handheld proxy capable of changing its rotational inertia by moving a weight along one axis at a high speed. Two experiments were conducted to evaluate the ability of Unident to provide users with impact sensations. In the first experiment, we demonstrate that Unident can physically provide an impact sensation applied to a handheld object by analyzing the pressure on the user's palm. The second experiment shows that Unident can provide an impact sensation with various magnitudes depending on the amount of rotational inertia to be changed. Finally, we present an application that can be enabled by Unident.

Humans can estimate the shape of a wielded object through the illusory feeling of the mass properties of the object obtained using their hands. Even though the shape of hand-held objects influences immersion and realism in virtual reality (VR), it is difficult to design VR controllers for rendering desired shapes according to the perceptions derived from the illusory effects of mass properties and shape perception. We propose Transcalibur, which is a hand-held VR controller that can render a 2D shape by changing its mass properties on a 2D planar area. We built a computational perception model using a data-driven approach from the collected data pairs of mass properties and perceived shapes. This enables Transcalibur to easily and effectively provide convincing shape perception based on complex illusory effects. Our user study showed that the system succeeded in providing the perception of various desired shapes in a virtual environment.