During object manipulation, we use visual, kinesthetic and tactile information to estimate different mechanical properties which characterize the object. For example, while lifting an object, we estimate its weight by integrating visual-based weight prediction with force feedback and skin deformation that we experienced during the lift. While we can precisely indicate the types of information which are available for weight estimation, the mechanism for forming this estimation is still unknown. One way to examine this question is by manipulating the sensory information available for the somatosensory system such as in the case of the size-weight illusion. In this illusion, participants lifting objects of different sizes perceive the smaller of two equally weighted objects to be heavier. Such perceptual bias provides evidence for the characteristics lying at the basis of the computational mechanism of weight estimation. To further reveal characteristics of sensory integration that generate this illusion, we built a haptic augmented virtual reality system that mimics the physical object lifting task while allowing us to investigate the relative contributions of specific feedback modalities as well as the effects of timing of the availability of the respective information. In multiple experiments, participants grasped and lifted two virtual objects and were tasked to report which object they perceived to be heavier. We show that consistent with previous real-world experiments, the size-weight illusion could be elicited, producing a shift in the point of subjective equality (PSE). Furthermore, a control experiment showed no shift in weight perception if reference and control objects were identical in size. Based on these results we propose further experiments that aim to induce perceptual illusions based on the manipulation of tactile information using an integrated skin stretch device.     «

During object manipulation, we use visual, kinesthetic and tactile information to estimate different mechanical properties which characterize the object. For example, while lifting an object, we estimate its weight by integrating visual-based weight prediction with force feedback and skin deformation that we experienced during the lift. While we can precisely indicate the types of information which are available for weight estimation, the mechanism for forming this estimation is still unknown....     »