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

Document Type

Conference Paper

Publication Date


Publication Title

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


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.


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