System Identification for 3D Force Control of a Human Arm Neuroprosthesis using Functional Electrical Stimulation

Authors

Eric M. Schearer, Cleveland State UniversityFollow
Yu-Wei Liao, Northwestern University
Eric J. Perreault, Northwestern University
Matthew C. Tresch, Northwestern University
William D. Memberg, Case Western Reserve University
Robert F. Kirsch, Case Western Reserve University
Kevin M. Lynch, Northwestern University

Document Type

Conference Paper

Publication Date

5-2012

Publication Title

Robotics and Automation (ICRA), 2012 IEEE International Conference on

Abstract

We present a method for controlling a neuroprosthesis for a paralyzed human arm using functional electrical stimulation (FES). The subject has surgically implanted electrodes for stimulating muscles in her shoulder and arm. Using input/output data, a model is identified that describes the mapping from muscle stimulations to the endpoint force measured at the subject’s hand. To compute the muscle stimulations given a target endpoint force the model is inverted. Because the system is redundant, we compute the inverse by minimizing muscle activations and use this inverse for feedforward control. This is the first published demonstration with a human subject with a high spinal cord injury of an FES controller that treats the arm with shoulder and elbow as a multiple-input multiple-output system and can achieve arbitrary goals.

Comments

This work was supported by NSF grant 0932263 and NSF Graduate Fellowship DGE-0824162.

Recommended Citation

Schearer, E. M., Yu-Wei Liao, Perreault, E. J., 2012, "System identification for 3D force control of a human arm neuroprosthesis using functional electrical stimulation," Robotics and Automation (ICRA), 2012 IEEE International Conference on, pp. 3698-3705.

DOI

10.1109/ICRA.2012.6224981