Intelligent Control of a Spinal Prosthesis to Restore Walking After Neural Injury: Recent Work and Future Possibilities

Abstract

This review focuses on the development of intelligent, intuitive control strategies for restoring walking using an innovative spinal neural prosthesis called intraspinal microstimulation (ISMS). These control strategies are inspired by the control of walking by the nervous system and are aimed at mimicking the natural functionality of locomotor-related sensorimotor systems. The work to date demonstrates how biologically inspired control strategies, some including machine learning methods, can be used to augment remaining function in models of complete and partial paralysis developed in anesthetized cats. This review highlights the advantages of learning predictions to produce automatically adaptive control of over-ground walking. This review also speculates on the possible future applications of similar machine learning algorithms for challenging walking tasks including navigating obstacles and traversing difficult terrain. Finally, this review explores the potential for plasticity and motor recovery with long-term use of such intelligent control systems and neural interfaces.