Multi Degree of Freedom Hybrid FES and Robotic Control of the Upper Limb.

Individuals who have suffered a spinal cord injury often require assistance to complete daily activities, and for individuals with tetraplegia, recovery of upper-limb function is among their top priorities. Hybrid functional electrical stimulation (FES) and exoskeleton systems have emerged as a potential solution to provide upper limb movement assistance. These systems leverage the user's own muscles via FES and provide additional movement support via an assistive exoskeleton.

Data-Driven Dynamic Motion Planning for Practical FES-Controlled Reaching Motions in Spinal Cord Injury.

Functional electrical stimulation (FES) is a promising technology for restoring reaching motions to individuals with upper-limb paralysis caused by a spinal cord injury (SCI). However, the limited muscle capabilities of an individual with SCI have made achieving FES-driven reaching difficult. We developed a novel trajectory optimization method that used experimentally measured muscle capability data to find feasible reaching trajectories.

Hybrid FES-exoskeleton control: Using MPC to distribute actuation for elbow and wrist movements.

Introduction: Individuals who have suffered a cervical spinal cord injury prioritize the recovery of upper limb function for completing activities of daily living. Hybrid FES-exoskeleton systems have the potential to assist this population by providing a portable, powered, and wearable device; however, realization of this combination of technologies has been challenging. In particular, it has been difficult to show generalizability across motions, and to define optimal distribution of actuation, given the complex nature of the combined dynamic system.

Shared Control of Elbow Movements with Functional Electrical Stimulation and Exoskeleton Assistance.

Individuals who suffer from paralysis as a result of a spinal cord injury list restoration of arm and hand function as a top priority. FES helps restore movement using the user's own muscles, but does not produce accurate and repeatable movements necessary for many functional tasks. Robots can assist users in achieving accurate and repeatable movements, but often require bulky hardware to generate the necessary torques.

Proof-of-Concept: A Hands-Free Interface for Robot-Assisted Self-Feeding.

Eating and drinking is an essential part of every-day life. And yet, there are many people in the world today who rely on others to feed them. In this work, we present a prototype robot-assisted self-feeding system for individuals with movement disorders.

Controlling an effector with eye movements: The effect of entangled sensory and motor responsibilities.

Restoring arm and hand function has been indicated by individuals with tetraplegia as one of the most important factors for regaining independence. The overall goal of our research is to develop assistive technologies that allow individuals with tetraplegia to control functional reaching movements. This study served as an initial step toward our overall goal by assessing the feasibility of using eye movements to control the motion of an effector in an experimental environment.

A review of methods for achieving upper limb movement following spinal cord injury through hybrid muscle stimulation and robotic assistance.

Individuals with tetraplegia, typically attributed to spinal cord injuries (SCI) at the cervical level, experience significant health care costs and loss of independence due to their limited reaching and grasping capabilities. Neuromuscular electrical stimulation (NMES) is a promising intervention to restore arm and hand function because it activates a person's own paralyzed muscles; however, NMES sometimes lacks the accuracy and repeatability necessary to position the limb for functional tasks, and repeated muscle stimulation can lead to fatigue. Robotic devices have the potential to restore function when used as assistive devices to supplement or replace limited or lost function of the upper limb following SCI.

Predicting functional force production capabilities of upper extremity functional electrical stimulation neuroprostheses: a proof of concept study.

Objective: This study's goal was to demonstrate person-specific predictions of the force production capabilities of a paralyzed arm when actuated with a functional electrical stimulation (FES) neuroprosthesis. These predictions allow us to determine, for each hand position in a person's workspace, if FES activated muscles can produce enough force to hold the arm against gravity and other passive forces, the amount of force the arm can potentially exert on external objects, and in which directions FES can move the arm.

Approach: We computed force production predictions for a person with high tetraplegia and an FES neuroprosthesis used to activate muscles in her shoulder and arm.

Developing a Quasi-Static Controller for a Paralyzed Human Arm: A Simulation Study.

Individuals with paralyzed limbs due to spinal cord injuries lack the ability to perform the reaching motions necessary to every day life. Functional electrical stimulation (FES) is a promising technology for restoring reaching movements to these individuals by reanimating their paralyzed muscles. We have proposed using a quasi-static model-based control strategy to achieve reaching controlled by FES.

Holding Static Arm Configurations With Functional Electrical Stimulation: A Case Study.

Functional electrical stimulation (FES) is a promising solution for restoring functional motion to individuals with paralysis, but the potential for achieving any desired full-arm reaching motion has not been realized. We present a combined feedforward-feedback controller capable of automatically calculating and applying the necessary muscle stimulations to hold the wrist of an individual with high tetraplegia in a desired static position. We used the controller to hold a complete arm configuration to maintain a series of static wrist positions.

Evaluating an open-loop functional electrical stimulation controller for holding the shoulder and elbow configuration of a paralyzed arm.

Functional electrical stimulation (FES) is a promising solution for restoring functional motion to individuals with paralysis, but the potential for achieving full-arm reaching motions with FES for various desired tasks has not been realized. We present an open-loop controller capable of calculating and applying the necessary muscle stimulations to hold the wrist of an individual with high tetraplegia at any desired position. We used the controller to hold the wrist at a series of static positions.

Semiparametric Identification of Human Arm Dynamics for Flexible Control of a Functional Electrical Stimulation Neuroprosthesis.

We present a method to identify the dynamics of a human arm controlled by an implanted functional electrical stimulation neuroprosthesis. The method uses Gaussian process regression to predict shoulder and elbow torques given the shoulder and elbow joint positions and velocities and the electrical stimulation inputs to muscles. We compare the accuracy of torque predictions of nonparametric, semiparametric, and parametric model types.

Multi-muscle FES force control of the human arm for arbitrary goals.

We present a method for controlling a neuroprosthesis for a paralyzed human arm using functional electrical stimulation (FES) and characterize the errors of the controller. The subject has surgically implanted electrodes for stimulating muscles in her shoulder and arm. Using input/output data, a model mapping muscle stimulations to isometric endpoint forces measured at the subject's hand was identified.

Modeling open-loop stability of a human arm driven by a functional electrical stimulation neuroprosthesis.

Functional electrical stimulation (FES) can be used to restore movement control following paralysis. For complex multijoint systems, it is becoming increasingly apparent that closed-loop controllers are needed. Designing a closed-loop control system is easiest when the open-loop system is stable.

Optimal sampling of recruitment curves for functional electrical stimulation control.

A major challenge in controlling multiple-input multiple output functional electrical stimulation systems is the large amount of time required to identify a workable system model due to the high dimensionality of the space of inputs. To address this challenge we are exploring optimal methods to sample the input space. In this paper we present two methods for optimally sampling isometric muscle force recruitment curves.