Sign in
NeuroscienceScientific Reports
Peer-reviewed journal article

Embodiment of Supernumerary Robotic Limbs in Virtual Reality

Ken Ichi AraiiD, Hiroto SaitoiD, Masaaki FukuokaiD, Sachiyo UedaiD, Maki SugimotoiD, Michiteru KitazakiiD, Masahiko İnamiiD

Abstract

The supernumerary robotic limb system expands the motor function of human users by adding extra artificially designed limbs. It is important for us to embody the system as if it is a part of ones own body and to maintain cognitive transparency in which the cognitive load is suppressed. Embodiment studies have been conducted with an expansion of bodily functions through a "substitution" and "extension." However, there have been few studies on the "addition" of supernumerary body parts. In this study, we developed a supernumerary robotic limb system that operates in a virtual environment, and then evaluated whether the extra limb can be regarded as a part of ones own body using a questionnaire and whether the perception of peripersonal space changes with a visuotactile crossmodal congruency task. We found that the participants can embody the extra-limbs after using the supernumerary robotic limb system. We also found a positive correlation between the perceptual change in the crossmodal congruency task and the subjective feeling that the number of ones arms had increased (supernumerary limb sensation). These results suggest that the addition of an extra body part may cause the participants to feel that they had acquired a new body part that differs from their original body part through a functional expansion.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
49
FWCI
4.20
Field percentile
top 5%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISSykes '25Umezawa '22Kannape '18Porssut '22Delahaye '23Kulu '16
80% semantic matchNeuroscience
John J. Sykes, Francesca Genovese, Elena Mussini+5 more·bioRxiv·Aug 1, 2025