Proprioception from a neurally controlled lower-extremity prosthesis

• Published in: Science translational medicine Vol. 10; no. 443
• Main Authors: Clites, Tyler R, Carty, Matthew J, Ullauri, Jessica B, Carney, Matthew E, Mooney, Luke M, Duval, Jean-François, Srinivasan, Shriya S, Herr, Hugh M
• Format: Journal Article
• Language: English
• Published: United States 30.05.2018
• ISSN: 1946-6242
• DOI: 10.1126/scitranslmed.aap8373

Humans can precisely sense the position, speed, and torque of their body parts. This sense is known as proprioception and is essential to human motor control. Although there have been many attempts to create human-mechatronic interactions, there is still no robust, repeatable methodology to reflect proprioceptive information from a synthetic device onto the nervous system. To address this shortcoming, we present an agonist-antagonist myoneural interface (AMI). The AMI is composed of (i) a surgical construct made up of two muscle-tendons-an agonist and an antagonist-surgically connected in series so that contraction of one muscle stretches the other and (ii) a bidirectional efferent-afferent neural control architecture. The AMI preserves the dynamic muscle relationships that exist within native anatomy, thereby allowing proprioceptive signals from mechanoreceptors within both muscles to be communicated to the central nervous system. We surgically constructed two AMIs within the residual limb of a subject with a transtibial amputation. Each AMI sends control signals to one joint of a two-degree-of-freedom ankle-foot prosthesis and provides proprioceptive information pertaining to the movement of that joint. The AMI subject displayed improved control over the prosthesis compared to a group of four subjects having traditional amputation. We also show natural reflexive behaviors during stair ambulation in the AMI subject that do not appear in the cohort of subjects with traditional amputation. In addition, we demonstrate a system for closed-loop joint torque control in AMI subjects. These results provide a framework for integrating bionic systems with human physiology.