Cybernetic Interfaces for the Restoration of Human Movement through Functional Electrical Stimulation

Abstract:

Functional electrical stimulation (FES) is a promising technology for activating muscles in spinal cord injured (SCI) patients. The objective of our project is to develop an intuitive user interface and control system that allows high--level tetraplegic patients to regain the use of their own arm. This work will have two primary outcomes: the development of a new technology that dramatically impacts the lives of SCI patients, and the development of biologically--inspired design principles for cyber--physical systems. The project can be broadly divided into two components: decoder development for determining how the subjects wish to move their arm, and controller development for getting the arm to the desired location. We are using both human and animal models for each of these project components, allowing us to investigate both the practical issues relevant to our current human subjects, and longer term questions dependent on the development of more robust cyber--physical interfaces for FES control. During the past year, we have been evaluating our developed systems on individuals with SCI. The multimodal decoder we have developed has been demonstrated to work well for individuals with a broad range of high cervical SCIs, allowing them to control arm movements throughout the reachable workspace. Furthermore, the system we developed has allowed us to address important questions regarding the role of congruent proprioceptive feedback in the ability to control user--machine interfaces. We also have made further progress towards controller development. We have demonstrated a technique for selecting which muscles to stimulate that minimizes physiological effort while guaranteeing arm stability during contact with the environment. We also are working towards progressing from the isometric force control demonstrated previously to dynamic motion control. This year, we developed a novel system identification technique that allows us to estimate plant dynamics with small amounts of data, as is needed to model--based feedback control.