Using Functional Electrical Stimulation Mediated by Iterative Learning Control and Robotics to Improve Arm Movement for People With Multiple Sclerosis.

Few interventions address multiple sclerosis (MS) arm dysfunction but robotics and functional electrical stimulation (FES) appear promising. This paper investigates the feasibility of combining FES with passive robotic support during virtual reality (VR) training tasks to improve upper limb function in people with multiple sclerosis (pwMS). The system assists patients in following a specified trajectory path, employing an advanced model-based paradigm termed iterative learning control (ILC) to adjust the FES to improve accuracy and maximise voluntary effort. Reaching tasks were repeated six times with ILC learning the optimum control action from previous attempts. A convenience sample of five pwMS was recruited from local MS societies, and the intervention comprised 18 one-hour training sessions over 10 weeks. The accuracy of tracking performance without FES and the amount of FES delivered during training were analyzed using regression analysis. Clinical functioning of the arm was documented before and after treatment with standard tests. Statistically significant results following training included: improved accuracy of tracking performance both when assisted and unassisted by FES; reduction in maximum amount of FES needed to assist tracking; and less impairment in the proximal arm that was trained. The system was well tolerated by all participants with no increase in muscle fatigue reported. This study confirms the feasibility of FES combined with passive robot assistance as a potentially effective intervention to improve arm movement and control in pwMS and provides the basis for a follow-up study.

Computational models of upper-limb motion during functional reaching tasks for application in FES-based stroke rehabilitation.

Functional electrical stimulation (FES) has been shown to be an effective approach to upper-limb stroke rehabilitation, where it is used to assist arm and shoulder motion. Model-based FES controllers have recently confirmed significant potential to improve accuracy of functional reaching tasks, but they typically require a reference trajectory to track. Few upper-limb FES control schemes embed a computational model of the task; however, this is critical to ensure the controller reinforces the intended movement with high accuracy. This paper derives computational motor control models of functional tasks that can be directly embedded in real-time FES control schemes, removing the need for a predefined reference trajectory. Dynamic models of the electrically stimulated arm are first derived, and constrained optimisation problems are formulated to encapsulate common activities of daily living. These are solved using iterative algorithms, and results are compared with kinematic data from 12 subjects and found to fit closely (mean fitting between 63.2% and 84.0%). The optimisation is performed iteratively using kinematic variables and hence can be transformed into an iterative learning control algorithm by replacing simulation signals with experimental data. The approach is therefore capable of controlling FES in real time to assist tasks in a manner corresponding to unimpaired natural movement. By ensuring that assistance is aligned with voluntary intention, the controller hence maximises the potential effectiveness of future stroke rehabilitation trials.

The application of precisely controlled functional electrical stimulation to the shoulder, elbow and wrist for upper limb stroke rehabilitation: a feasibility study.

BACKGROUND: Functional electrical stimulation (FES) during repetitive practice of everyday tasks can facilitate recovery of upper limb function following stroke. Reduction in impairment is strongly associated with how closely FES assists performance, with advanced iterative learning control (ILC) technology providing precise upper-limb assistance. The aim of this study is to investigate the feasibility of extending ILC technology to control FES of three muscle groups in the upper limb to facilitate functional motor recovery post-stroke. METHODS: Five stroke participants with established hemiplegia undertook eighteen intervention sessions, each of one hour duration. During each session FES was applied to the anterior deltoid, triceps, and wrist/finger extensors to assist performance of functional tasks with real-objects, including closing a drawer and pressing a light switch. Advanced model-based ILC controllers used kinematic data from previous attempts at each task to update the FES applied to each muscle on the subsequent trial. This produced stimulation profiles that facilitated accurate completion of each task while encouraging voluntary effort by the participant. Kinematic data were collected using a Microsoft Kinect, and mechanical arm support was provided by a SaeboMAS. Participants completed Fugl-Meyer and Action Research Arm Test clinical assessments pre- and post-intervention, as well as FES-unassisted tasks during each intervention session. RESULTS: Fugl-Meyer and Action Research Arm Test scores both significantly improved from pre- to post-intervention by 4.4 points. Improvements were also found in FES-unassisted performance, and the amount of arm support required to successfully perform the tasks was reduced. CONCLUSIONS: This feasibility study indicates that technology comprising low-cost hardware fused with advanced FES controllers accurately assists upper limb movement and may reduce upper limb impairments following stroke.

Electrical stimulation and iterative learning control for functional recovery in the upper limb post-stroke.

Therapies using functional electrical stimulation (FES) in conjunction with practice of everyday tasks have proven effective in facilitating recovery of upper limb function following stroke. The aim of the current study is to develop a multi-channel electrical stimulation system that precisely controls the assistance provided in goal-orientated tasks through use of advanced model-based 'iterative learning control' (ILC) algorithms to facilitate functional motor recovery of the upper limb post-stroke. FES was applied to three muscle groups in the upper limb (the anterior deltoid, triceps and wrist extensors) to assist hemiparetic, chronic stroke participants to perform a series of functional tasks with real objects, including closing a drawer, turning on a light switch and repositioning an object. Position data from the participants' impaired upper limb was collected using a Microsoft Kinect® and was compared to an ideal reference. ILC used data from previous attempts at the task to moderate the FES signals applied to each muscle group on a trial by trial basis to reduce performance error whilst supporting voluntary effort by the participant. The clinical trial is on-going. Preliminary results show improvements in performance accuracy for each muscle group, as well as improvements in clinical outcome measures pre and post 18 training sessions. Thus, the feasibility of applying precisely controlled FES to three muscle groups in the upper limb to facilitate functional reach and grasp movements post stroke has been demonstrated.

A personalized sensor-controlled microstimulator system for arm rehabilitation poststroke. Part 2: Objective outcomes and patients' perspectives.

OBJECTIVE: To examine the effect of home-based electrical stimulation using closed-loop control of implanted microstimulators on upper limb function and impairment, and subjects' perception of the system. MATERIALS AND METHODS: Six subjects with poststroke hemiparesis, and reduced upper limb function, who had taken part in Phase 1 of the study, were fitted with a personalized closed-loop control system (Phase 2) and used it at home during performance of functional tasks for 12 weeks (Phase 3). Main outcome measures were: Action Research Arm Test (ARAT), Fugl-Meyer upper limb assessment (FMA), and motor control (Tracking Index). Subjects' perception of the system was assessed in a structured interview. RESULTS: Improvement in ARAT (p=0.05), FMA (p=0.02), and Tracking Index (p=0.03) during Phase 3. Five subjects said using the system had changed their lives and improved their function, all performed functional tasks with the system, but external components were inconvenient. CONCLUSIONS: Closed-loop control improved in function. Subjective assessment identified that the external sensors were effective.

Stroke participants' perceptions of robotic and electrical stimulation therapy: a new approach.

PURPOSE: User perceptions are critical, yet often ignored factors in the design and development of rehabilitation technologies. In this article, measures for collection of patient perceptions are developed and applied to a novel upper limb workstation that combines robotic therapy and electrical stimulation (ES). METHOD: Five participants with chronic upper limb hemiplegia post-stroke used a robotic workstation to undertake supported tracking tasks augmented by precisely controlled ES to their triceps muscle. Following a 6 week trial, a purpose designed set of questions was developed and individual interviews were conducted by an independent health psychologist. RESULTS: The simple, quick to administer question set showed that participants had a positive response to the system, and contributed valuable feedback with regard to its usability and effectiveness. Participants want a home-based system targeting their whole arm. CONCLUSION: This article demonstrates the value in assessing user perceptions of a rehabilitation system via a simple question set. While the results of this study have implications for a wider audience, our recommendations are for a qualitative study to develop a generic evaluation tool which could be used across the growing number of devices to provide feedback to enhance future development of any new technology for rehabilitation.

Potential for new technologies in clinical practice.

PURPOSE OF REVIEW: Cost-effective neurorehabilitation is essential owing to financial constraints on healthcare resources. Technologies have the potential to contribute but without strong clinical evidence are unlikely to be widely reimbursed. This review presents evidence of new technologies since 2008 and identifies barriers to translation of technologies into clinical practice. RECENT FINDINGS: Technology has not been shown to be superior to intensively matched existing therapies. Research has been undertaken into the development and preliminary clinical testing of novel technologies including robotics, electrical stimulation, constraint-induced movement therapy, assistive orthoses, noninvasive brain stimulation, virtual reality and gaming devices. Translation of the research into clinical practice has been impeded by a lack of robust evidence of clinical effectiveness and usability. Underlying mechanisms associated with recovery are beginning to be explored, which may lead to more targeted interventions. Improvements in function have been demonstrated beyond the normal recovery period, but few trials demonstrate lasting effects. SUMMARY: Technologies, alone or combined, may offer a cost-effective way to deliver intensive neurorehabilitation therapy in clinical and community environments, and have the potential to empower patients to take more responsibility for their rehabilitation and continue with long-term exercise.

A model of the upper extremity using FES for stroke rehabilitation.

A model of the upper extremity is developed in which the forearm is constrained to lie in a horizontal plane and electrical stimulation is applied to the triceps muscle. Identification procedures are described to estimate the unknown parameters using tests that can be performed in a short period of time. Examples of identified parameters obtained experimentally are presented for both stroke patients and unimpaired subjects. A discussion concerning the identification's repeatability, together with results confirming the accuracy of the overall representation, is given. The model has been used during clinical trials in which electrical stimulation is applied to the triceps muscle of a number of stroke patients for the purpose of improving both their performance at reaching tasks and their level of voluntary control over their impaired arm. Its purpose in this context is threefold: Firstly, changes occurring in the levels of stiffness and spasticity in each subject's arm can be monitored by comparing frictional components of models identified at different times during treatment. Secondly, the model is used to calculate the moments applied during tracking tasks that are due to a patient's voluntary effort, and it therefore constitutes a useful tool with which to analyze their performance. Thirdly, the model is used to derive the advanced controllers that govern the level of stimulation applied to subjects over the course of the treatment. Details are provided to show how the model is applied in each case, and sample results are shown.

Therapeutic effectiveness of electric stimulation of the upper-limb poststroke using implanted microstimulators.

OBJECTIVE: To investigate the therapeutic effect of functional exercise augmented by programmable implanted microstimulators on arm and hand function. DESIGN: Before and after study. SETTING: Implantation was performed in a neurosurgery unit, systems were programmed, and tests were conducted in a university laboratory and subjects exercised at home. PARTICIPANTS: Hemiparetic subjects (N=7) with reduced upper-limb function who were at least 12 months poststroke were recruited from the community. No subjects withdrew. INTERVENTION: Microstimulators were implanted into the arms and forearms to activate elbow, wrist, and finger extension, and thumb abduction. After training and programming of the system, subjects underwent 12 weeks of functional home-based exercise with stimulation. MAIN OUTCOME MEASURES: The primary functional measure was the Action Research Arm Test (ARAT). Impairment measures included upper-limb Fugl-Meyer Assessment (FMA) and tests of motor control (tracking index), spasticity (electromyography stretch index) strength, and active range of motion (AROM). The assessor was not blinded, but scores were validated by an independent blinded observer. RESULTS: All subjects were able to perform functional activities at home by using the system. Compliance was excellent, and there were no serious adverse events. Statistically significant improvements were measured (P<.05) in the tracking index (57.3 degrees(2)+/-48.65 degrees(2)), FMA score (6.3+/-3.59), wrist-extensor strength (5.5+/-4.37 N), and wrist AROM (19.3 degrees +/-18.96 degrees). The mean improvement in ARAT score +/- SD of 4.9+/-7.89 was not statistically significant. CONCLUSIONS: This study has shown the feasibility of a programmable implanted microstimulator system used at home to perform functional exercises and a reduction in impairment after 12 weeks.