Achieving Practical Functional Electrical Stimulation-driven Reaching Motions In An Individual With Tetraplegia

Functional electrical stimulation (FES) is a promising technique for restoring the ability to complete reaching motions to individuals with tetraplegia due to a spinal cord injury (SCI). FES has proven to be a successful technique for controlling many functional tasks such as grasping, standing, and even limited walking. However, translating these successes to reaching motions has proven difficult due to the complexity of the arm and the goaldirected nature of reaching motions. The state-of-the-art systems either use robots to assist the FES-driven reaching motions or control the arm of healthy subjects to complete planar motions. These controllers do not directly translate to controlling the full-arm of an individual with tetraplegia because the muscle capabilities of individuals with spinal cord injuries are unique and often limited due to muscle atrophy and the loss of function caused by lower motor neuron damage. This dissertation aims to develop a full-arm FES-driven reaching controller that is capable of achieving 3D reaching motions in an individual with a spinal cord injury. Aim 1 was to develop a complete-arm FES-driven reaching controller that can hold static hand positions for an individual with high tetraplegia due to SCI. We developed a combined feedforward-feedback controller which used the subject-specific model to automatically determine the muscle stimulation commands necessary to hold a desired static hand position. Aim 2 was to develop a subject-specific model-based control strategy to use FES to drive the arm of an individual with high tetraplegia due to SCI along a desired path in the subject’s workspace. We used trajectory optimization to find feasible trajectories which explicitly account for the unique muscle characteristics and the simulated arm dynamics of our subject with tetraplegia. We then developed a model predictive control controller to iii control the arm along the desired trajectory. The controller developed in this dissertation is a significant step towards restoring full arm reaching function to individuals with spinal cord injuries

Artificial Motor Control For Electrically Stimulated Upper Limbs Of Plegic Or Paretic People

Functional Electrical Stimulation (FES) is a technique used in the restoration and generation of movements performed by subjects with neuromuscular disorders such as spinal cord injury (SCI). The purpose of this article is to outline the state of the art and perspectives of the use of FES in artificial motor control of the upper limbs in paretic or plegic people. Methods: The databases used in papers selection were Google Scholar and Capes’ Portals as well as proceedings of the Annual Conference of the International Functional Electrical Stimulation Society (IFESS). Results: Approximately 85% of the reviewed studies showed FES profile with pulse duration ranging from 1 to 300 μs and modulating (burst) frequency between 10 and 40 Hz. Regarding the type of electrodes, 88% of the studies employed transcutaneous electrodes. Conclusion: We concluded that FES with closed-loop feedback and feedforward are the most used and most viable systems for upper limbs motor control, because they perform self-corrections slowing neuromuscular adaptation, allowing different planes and more range of movement and sensory-motor integration. One of the difficulties found in neuroprosthesis systems are electrical wires attached to the user, becoming uninteresting in relation to aesthetics and break. The future perspectives lead to a trend to miniaturization of the stimulation equipment and the availability of wireless networks, which allow the attachment of modules to other components without physical contact, and will become more attractive for daily use. © 2016, Sociedade Brasileira de Engenharia Biomedica. All rights reserved.32219921

Feasibility of Using an Equilibrium Point Strategy to Control Reaching Movements of Paralyzed Arms with Functional Electrical Stimulation

Functional electrical stimulation (FES) is a technology capable of improving the quality of life for those with the loss of limb movement related to spinal cord injuries. Individuals with high-level tetraplegia, in particular, have lost all movement capabilities below the neck. FES has shown promise in bypassing spinal cord damage by sending electrical impulses directly to a nerve or muscle to trigger a desired function. Despite advancements in FES, full-arm reaching motions have not been achieved, leaving patients unable to perform fundamental tasks such as eating and grooming. To overcome the inability in current FES models to achieve multi-joint coordination, a controller utilizing muscle activations to achieve full-arm reaching motions using equilibrium point control on a computer-simulated human arm was developed. Initial simulations performed on the virtual arm generated muscle activations and joint torques required to hold a static position. This data was used as a model for Gaussian Process Regression to obtain muscle activations required to hold any desired static position. The accuracy of the controller was tested on twenty joint positions and was capable of holding the virtual arm within a mean of 1.1 ± 0.13 cm from an original target position. Once held in a static position, external forces were introduced to the simulation to evaluate if muscle activations returned the arm towards the original position after being moved away within a basin of attraction. It was found that the basin of attraction was limited to a 15 cm sphere around the joint position, regardless of position in the workspace. Muscle activations were then tested and found to successfully perform movements between points within the basin. The development of a controller capable of equilibrium point controlled movement is the initial step in recreating these movements in high-level tetraplegia patients with an implanted FES

Feasibility of Using an Equilibrium Point Strategy to Control Reaching Movements of Paralyzed Arms with Functional Electrical Stimulation

Functional electrical stimulation (FES) is a technology capable of improving the quality of life for those with the loss of limb movement related to spinal cord injuries. Individuals with high-level tetraplegia, in particular, have lost all movement capabilities below the neck. FES has shown promise in bypassing spinal cord damage by sending electrical impulses directly to a nerve or muscle to trigger a desired function. Despite advancements in FES, full-arm reaching motions have not been achieved, leaving patients unable to perform fundamental tasks such as eating and grooming. To overcome the inability in current FES models to achieve multi-joint coordination, a controller utilizing muscle activations to achieve full-arm reaching motions using equilibrium point control on a computer-simulated human arm was developed. Initial simulations performed on the virtual arm generated muscle activations and joint torques required to hold a static position. This data was used as a model for Gaussian Process Regression to obtain muscle activations required to hold any desired static position. The accuracy of the controller was tested on twenty joint positions and was capable of holding the virtual arm within a mean of 1.1 ± 0.13 cm from an original target position. Once held in a static position, external forces were introduced to the simulation to evaluate if muscle activations returned the arm towards the original position after being moved away within a basin of attraction. It was found that the basin of attraction was limited to a 15 cm sphere around the joint position, regardless of position in the workspace. Muscle activations were then tested and found to successfully perform movements between points within the basin. The development of a controller capable of equilibrium point controlled movement is the initial step in recreating these movements in high-level tetraplegia patients with an implanted FES

Toward the Restoration of Hand Use to a Paralyzed Monkey: Brain-Controlled Functional Electrical Stimulation of Forearm Muscles

Loss of hand use is considered by many spinal cord injury survivors to be the most devastating consequence of their injury. Functional electrical stimulation (FES) of forearm and hand muscles has been used to provide basic, voluntary hand grasp to hundreds of human patients. Current approaches typically grade pre-programmed patterns of muscle activation using simple control signals, such as those derived from residual movement or muscle activity. However, the use of such fixed stimulation patterns limits hand function to the few tasks programmed into the controller. In contrast, we are developing a system that uses neural signals recorded from a multi-electrode array implanted in the motor cortex; this system has the potential to provide independent control of multiple muscles over a broad range of functional tasks. Two monkeys were able to use this cortically controlled FES system to control the contraction of four forearm muscles despite temporary limb paralysis. The amount of wrist force the monkeys were able to produce in a one-dimensional force tracking task was significantly increased. Furthermore, the monkeys were able to control the magnitude and time course of the force with sufficient accuracy to track visually displayed force targets at speeds reduced by only one-third to one-half of normal. Although these results were achieved by controlling only four muscles, there is no fundamental reason why the same methods could not be scaled up to control a larger number of muscles. We believe these results provide an important proof of concept that brain-controlled FES prostheses could ultimately be of great benefit to paralyzed patients with injuries in the mid-cervical spinal cord

A spinal cord neuroprosthesis for locomotor deficits due to Parkinson’s disease

People with late-stage Parkinson’s disease (PD) often suffer from debilitating locomotor deficits that are resistant to currently available therapies. To alleviate these deficits, we developed a neuroprosthesis operating in closed loop that targets the dorsal root entry zones innervating lumbosacral segments to reproduce the natural spatiotemporal activation of the lumbosacral spinal cord during walking. We first developed this neuroprosthesis in a non-human primate model that replicates locomotor deficits due to PD. This neuroprosthesis not only alleviated locomotor deficits but also restored skilled walking in this model. We then implanted the neuroprosthesis in a 62-year-old male with a 30-year history of PD who presented with severe gait impairments and frequent falls that were medically refractory to currently available therapies. We found that the neuroprosthesis interacted synergistically with deep brain stimulation of the subthalamic nucleus and dopaminergic replacement therapies to alleviate asymmetry and promote longer steps, improve balance and reduce freezing of gait. This neuroprosthesis opens new perspectives to reduce the severity of locomotor deficits in people with PD

Functional Electrical Stimulation mediated by Iterative Learning Control and 3D robotics reduces motor impairment in chronic stroke

Background: Novel stroke rehabilitation techniques that employ electrical stimulation (ES) and robotic technologies are effective in reducing upper limb impairments. ES is most effective when it is applied to support the patients’ voluntary effort; however, current systems fail to fully exploit this connection. This study builds on previous work using advanced ES controllers, and aims to investigate the feasibility of Stimulation Assistance through Iterative Learning (SAIL), a novel upper limb stroke rehabilitation system which utilises robotic support, ES, and voluntary effort. Methods: Five hemiparetic, chronic stroke participants with impaired upper limb function attended 18, 1 hour intervention sessions. Participants completed virtual reality tracking tasks whereby they moved their impaired arm to follow a slowly moving sphere along a specified trajectory. To do this, the participants’ arm was supported by a robot. ES, mediated by advanced iterative learning control (ILC) algorithms, was applied to the triceps and anterior deltoid muscles. Each movement was repeated 6 times and ILC adjusted the amount of stimulation applied on each trial to improve accuracy and maximise voluntary effort. Participants completed clinical assessments (Fugl-Meyer, Action Research Arm Test) at baseline and post-intervention, as well as unassisted tracking tasks at the beginning and end of each intervention session. Data were analysed using t-tests and linear regression. Results: From baseline to post-intervention, Fugl-Meyer scores improved, assisted and unassisted tracking performance improved, and the amount of ES required to assist tracking reduced. Conclusions: The concept of minimising support from ES using ILC algorithms was demonstrated. The positive results are promising with respect to reducing upper limb impairments following stroke, however, a larger study is required to confirm this

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. In a simulation based on a real-life individual with SCI, we compared our method to attempting to follow naive direct-to-target paths. We tested our trajectory planner with three control structures that are commonly used in applied FES: feedback, feedforward-feedback, and model predictive control. Overall, trajectory optimization improved the ability to reach targets and improved the accuracy for the feedforward-feedback and model predictive controllers (

MUNDUS project : MUltimodal neuroprosthesis for daily upper limb support

Background: MUNDUS is an assistive framework for recovering direct interaction capability of severely motor impaired people based on arm reaching and hand functions. It aims at achieving personalization, modularity and maximization of the user’s direct involvement in assistive systems. To this, MUNDUS exploits any residual control of the end-user and can be adapted to the level of severity or to the progression of the disease allowing the user to voluntarily interact with the environment. MUNDUS target pathologies are high-level spinal cord injury (SCI) and neurodegenerative and genetic neuromuscular diseases, such as amyotrophic lateral sclerosis, Friedreich ataxia, and multiple sclerosis (MS). The system can be alternatively driven by residual voluntary muscular activation, head/eye motion, and brain signals. MUNDUS modularly combines an antigravity lightweight and non-cumbersome exoskeleton, closed-loop controlled Neuromuscular Electrical Stimulation for arm and hand motion, and potentially a motorized hand orthosis, for grasping interactive objects. Methods: The definition of the requirements and of the interaction tasks were designed by a focus group with experts and a questionnaire with 36 potential end-users. Five end-users (3 SCI and 2 MS) tested the system in the configuration suitable to their specific level of impairment. They performed two exemplary tasks: reaching different points in the working volume and drinking. Three experts evaluated over a 3-level score (from 0, unsuccessful, to 2, completely functional) the execution of each assisted sub-action. Results: The functionality of all modules has been successfully demonstrated. User’s intention was detected with a 100% success. Averaging all subjects and tasks, the minimum evaluation score obtained was 1.13 ± 0.99 for the release of the handle during the drinking task, whilst all the other sub-actions achieved a mean value above 1.6. All users, but one, subjectively perceived the usefulness of the assistance and could easily control the system. Donning time ranged from 6 to 65 minutes, scaled on the configuration complexity. Conclusions: The MUNDUS platform provides functional assistance to daily life activities; the modules integration depends on the user’s need, the functionality of the system have been demonstrated for all the possible configurations, and preliminary assessment of usability and acceptance is promising