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

Combining electrical stimulation mediated by iterative learning control with movement practice using real objects and simulated tasks for post-stroke upper extremity rehabilitation.

Objective: Task specific training and Electrical Stimulation (ES) are techniques used in rehabilitation of the upper extremity post stroke. This study describes the feasibility of using a rehabilitation system that combines personalised, precisely controlled levels of ES to the anterior deltoid, triceps and finger and wrist extensors during goal-oriented activity utilising real objects from daily life. Materials and Methods:Four chronic stroke participants undertook seventeen intervention sessions, each of one hour duration. During each session, particpants performed goal -orientated tasks while Iterative learning control (ILC) updated the ESsignal applied to each muscle group. The update was based on the difference between the ideal and actual movement in the previous attempt at the task, measured using Microsoft Kinect and PrimeSense sensors. The control system applied the minimum amount of ES required with a view to facilitating success at each given task while maximising voluntary effort. Results: Preliminary results demonstrate that ES mediated by ILC resulted in a statistically significant improvement in range of movement in all four joint angles studied (shoulder flexion; elbow, wrist and index finger extension) over 17 intervention sessions. Additionally, participants required signficantly less extrinsic support for each task. The tasks and system is described and initial intervention data are reported. Discussion: The feasibility of using this system for assisting upper limb movement has been demonstrated. A large scale pilot RCT is now required

Optimisation of hand posture stimulation using an electrode array and iterative learning control.

Nonlinear optimisation-based search algorithms have been developed for the precise stimulation of muscles in the wrist and hand, to enable stroke patients to attain predefined gestures. These have been integrated in a system comprising a 40 element surface electrode array that is placed on the forearm, an electrogoniometer and data glove supplying position data from 16 joint angles, and custom signal generation and switching hardware to route the electrical stimulation to individual array elements. The technology will be integrated in a upper limb rehabilitation system currently undergoing clinical trials to increase their ability to perform functional tasks requiring fine hand and finger movement. Initial performance results from unimpaired subjects show the successful reproduction of six reference hand postures using the system

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

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

Development of user-friendly wearable electronic textiles for healthcare applications

This paper presents research into a user-friendly electronic sleeve (e-sleeve) with integrated electrodes in an array for wearable healthcare. The electrode array was directly printed onto an everyday clothing fabric using screen printing. The fabric properties and designed structures of the e-sleeve were assessed and refined through interaction with end users. Different electrode array layouts were fabricated to optimize the user experience in terms of comfort, effectivity and ease of use. The e-sleeve uses dry electrodes to facilitate ease of use and the electrode array can survive bending a sufficient number of times to ensure an acceptable usage lifetime. Different cleaning methods (washing and wiping) have been identified to enable reuse of the e-sleeve after contamination during use. The application of the e-sleeve has been demonstrated via muscle stimulation on the upper limb to achieve functional tasks (e.g., hand opening, pointing) for eight stroke survivors

Adaptive hybrid robotic system for rehabilitation of reaching movement after a brain injury: a usability study

BACKGROUND: Brain injury survivors often present upper-limb motor impairment affecting the execution of functional activities such as reaching. A currently active research line seeking to maximize upper-limb motor recovery after a brain injury, deals with the combined use of functional electrical stimulation (FES) and mechanical supporting devices, in what has been previously termed hybrid robotic systems. This study evaluates from the technical and clinical perspectives the usability of an integrated hybrid robotic system for the rehabilitation of upper-limb reaching movements after a brain lesion affecting the motor function. METHODS: The presented system is comprised of four main components. The hybrid assistance is given by a passive exoskeleton to support the arm weight against gravity and a functional electrical stimulation device to assist the execution of the reaching task. The feedback error learning (FEL) controller was implemented to adjust the intensity of the electrical stimuli delivered on target muscles according to the performance of the users. This control strategy is based on a proportional-integral-derivative feedback controller and an artificial neural network as the feedforward controller. Two experiments were carried out in this evaluation. First, the technical viability and the performance of the implemented FEL controller was evaluated in healthy subjects (N = 12). Second, a small cohort of patients with a brain injury (N = 4) participated in two experimental session to evaluate the system performance. Also, the overall satisfaction and emotional response of the users after they used the system was assessed. RESULTS: In the experiment with healthy subjects, a significant reduction of the tracking error was found during the execution of reaching movements. In the experiment with patients, a decreasing trend of the error trajectory was found together with an increasing trend in the task performance as the movement was repeated. Brain injury patients expressed a great acceptance in using the system as a rehabilitation tool. CONCLUSIONS: The study demonstrates the technical feasibility of using the hybrid robotic system for reaching rehabilitation. Patients’ reports on the received intervention reveal a great satisfaction and acceptance of the hybrid robotic system

Teachers’ and school leaders’ perceptions of commercialisation in Australian public schools

© 2017, The Australian Association for Research in Education, Inc. This paper explores teachers’ and school leaders’ perceptions of commercialisation in Australian public schools, reporting on findings from an open-ended survey question from an exploratory study that sought to investigate teacher and school leader perceptions and experiences of commercialisation. Commercialisation, for the purposes of this paper, is understood as the creation, marketing and sale of education goods and services to schools by for-profit providers and often includes (but is not limited to) the provision of curriculum content, assessment services, data infrastructures, digital learning, remedial instruction, professional development and school administration support. Our account highlights that commercialisation is prevalent in the day-to-day practice of Australian public schools. The perceptions of teachers and leaders suggest that commercialisation is complex, with both affordances and challenges. Respondents acknowledged that aspects of commercialisation are necessary for successfully running schools and classrooms in the 21st century, but also noted that there is a fine line beyond which these seemingly innocuous services become perilous. Concerns focused on how particular services are leading to the deprofessionalisation of teachers as they have less autonomy over what to teach and how to teach it. Moreover, teachers and school leaders reported being perturbed by the idea that commercial providers and services might work to replace teachers in the future. Drawing on these data we argue that growing commercialisation in Australian public schools clearly requires an ethical debate that schools, education professionals, policy makers and interested publics are yet to have

Using functional electrical stimulation mediated by iterative learning control and robotics to improve arm movement for people with Multiple Sclerosis

Abstract: 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

Iterative Learning Control for Electrical Stimulation and Stroke Rehabilitation

Iterative learning control (ILC) has its origins in the control of processes that perform a task repetitively with a view to improving accuracy from trial to trial by using information from previous executions of the task. This brief shows how a classic application of this technique – trajectory following in robots – can be extended to neurological rehabilitation after stroke. Regaining upper limb movement is an important step in a return to independence after stroke, but the prognosis for such recovery has remained poor. Rehabilitation robotics provides the opportunity for repetitive task-oriented movement practice reflecting the importance of such intense practice demonstrated by conventional therapeutic research and motor learning theory. Until now this technique has not allowed feedback from one practice repetition to influence the next, also implicated as an important factor in therapy. The authors demonstrate how ILC can be used to adjust external functional electrical stimulation of patients’ muscles while they are repeatedly performing a task in response to the known effects of stimulation in previous repetitions. As the motor nerves and muscles of the arm reaquire the ability to convert an intention to move into a motion of accurate trajectory, force and rapidity, initially intense external stimulation can now be scaled back progressively until the fullest possible independence of movement is achieved

Electrical Stimulation and Iterative Learning Control combined with real objects and simulated tasks to assist Motor Recovery in the Upper Extremity Post-Stroke

Evidence supports the combination of electrical stimulation (ES) and task specific training in rehabilitation of the upper extremity following stroke. The aim of this study is to develop a rehabilitation system that delivers precisely controlled levels of stimulation to the shoulder, elbow and wrist during goal-oriented activity utilising everyday real objects. Iterative learning control (ILC) is used to update the stimulation signal applied to each muscle group based on the error between the ideal and actual movement in the previous attempt. The control system applies the minimum amount of stimulation required, maximising voluntary effort with a view to facilitating success at each given task. Markerless motion tracking is provided via a Microsoft Kinect, and a Primesense. Preliminary results show that ES mediated by ILC has successfully facilitated movement across the shoulder, elbow and wrist of chronic stroke patients. Overall, joint error has reduced for all participants with the mean error across all joints showing reductions for all participants. Furthermore, there was a significant reduction in extrinsic support necessary for each task. The system is described and initial intervention data are reported