Partial Arm Weight Support Does Not Hamper the Weight Perception of Haptically-Rendered Virtual Objects: A Psychophysics Study

Arm weight support (AWS) from upper-limb exoskeletons aids training by reducing fatigue and increasing the movement workspace, especially in people with acquired brain injury (ABI). Simultaneously, task-specific training could be enabled via haptic rendering, simulating the interaction forces with tangible virtual objects. However, how AWS affects somatosensory perception, such as the perception of the weight of haptically rendered virtual objects, is unclear. We therefore conducted a psychophysics experiment with 40 participants investigating the effect of partial AWS on virtual object weight perception during dynamic lifting. Participants performed the lifting task under two conditions: with and without AWS, where AWS compensated for 50% of their arm weight. An upperlimb exoskeleton equipped with a haptic hand module provided both AWS and haptic rendering of virtual objects. The virtual objects and a representation of the participant's arm and hand were visualized using immersive virtual reality.Weight perception was assessed using just-noticeable differences (JNDs). To evaluate the experimental setup, participants' estimated elbow torques were analyzed. Additionally, subjective measures of task load, motivation, and user experience with the exoskeleton were collected to explore potential secondary factors influencing weight perception. We found that partial AWS effectively reduced elbow load during dynamic lifting compared to no-AWS. The JND was not significantly different between conditions, suggesting that AWS does not hamper weight discrimination. However, participants with a larger self-reported sense of control over their movement and those who reported that the robot followed their movements more closely were associated with better weight perception. Our findings suggest that including haptic rendering into exoskeletons that provide partial AWS could be a viable solution to provide task-specific training.