@article {Georgeeaax2352, author = {George, J. A. and Kluger, D. T. and Davis, T. S. and Wendelken, S. M. and Okorokova, E. V. and He, Q. and Duncan, C. C. and Hutchinson, D. T. and Thumser, Z. C. and Beckler, D. T. and Marasco, P. D. and Bensmaia, S. J. and Clark, G. A.}, title = {Biomimetic sensory feedback through peripheral nerve stimulation improves dexterous use of a bionic hand}, volume = {4}, number = {32}, elocation-id = {eaax2352}, year = {2019}, doi = {10.1126/scirobotics.aax2352}, publisher = {Science Robotics}, abstract = {We describe use of a bidirectional neuromyoelectric prosthetic hand that conveys biomimetic sensory feedback. Electromyographic recordings from residual arm muscles were decoded to provide independent and proportional control of a six-DOF prosthetic hand and wrist{\textemdash}the DEKA LUKE arm. Activation of contact sensors on the prosthesis resulted in intraneural microstimulation of residual sensory nerve fibers through chronically implanted Utah Slanted Electrode Arrays, thereby evoking tactile percepts on the phantom hand. With sensory feedback enabled, the participant exhibited greater precision in grip force and was better able to handle fragile objects. With active exploration, the participant was also able to distinguish between small and large objects and between soft and hard ones. When the sensory feedback was biomimetic{\textemdash}designed to mimic natural sensory signals{\textemdash}the participant was able to identify the objects significantly faster than with the use of traditional encoding algorithms that depended on only the present stimulus intensity. Thus, artificial touch can be sculpted by patterning the sensory feedback, and biologically inspired patterns elicit more interpretable and useful percepts.}, URL = {https://robotics.sciencemag.org/content/4/32/eaax2352}, eprint = {https://robotics.sciencemag.org/content/4/32/eaax2352.full.pdf}, journal = {Science Robotics} }