Objects feel stiffer in the nondominant hand when comparing between hands.

To estimate the stiffness of an object, such as when choosing a ripe fruit, we usually probe it with our hands. The mechanism of forming stiffness perception was widely explored in unimanual interactions with objects, but our understanding of forming stiffness perception in between the different hand interactions is limited. Here, we studied stiffness perception during the interaction with virtual elastic objects touched by different hands. Participants sequentially probed pairs of virtual elastic objects and reported which object felt stiffer. They either touched both objects with the same hand or touched each object with a different hand. When participants used the same hand to interact with the objects, they reliably distinguished differences in stiffness. However, when each object was touched with different hands, we found that the object that was explored using the nondominant hand was judged as stiffer than when touched with the dominant hand. That is, right-handed participants perceived objects touched with the left hand as stiffer than objects touched with the right hand, and left-handed participants perceived objects touched with the right hand as stiffer than objects touched with the left hand. These results contribute to the fundamental understanding of somatosensory perception in manual interactions and have implications for the design of bimanual interfaces in various applications, such as teleoperation systems and medical simulators.NEW & NOTEWORTHY This study reveals a perceptual bias in stiffness estimation during interaction with both hands. When participants sequentially touched two virtual objects with different hands, the object explored with the nondominant hand was consistently judged as stiffer. This effect was observed in both right- and left-handed participants. These findings uncover a lateralized bias in haptic perception, advancing our understanding of somatosensory processing and informing the design of bimanual human-machine interfaces such as teleoperation systems and surgical simulators.