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

Prediction of setup times for an advanced upper limb functional electrical stimulation system

Introduction: Rehabilitation devices take time to don, and longer or unpredictable setup time impacts on usage. This paper reports on the development of a model to predict setup time for upper limb functional electrical stimulation. Methods: Participants’ level of impairment (Fugl Meyer-Upper Extremity Scale), function (Action Research Arm Test) and mental status (Mini Mental Scale) were measured. Setup times for each stage of the setup process and total setup times were recorded. A predictive model of setup time was devised using upper limb impairment and task complexity. Results: Six participants with stroke were recruited, mean age 60 (�17) years and mean time since stroke 9.8 (�9.6) years. Mean Fugl Meyer-Upper Extremity score was 31.1 (�6), Action Research Arm Test 10.4 (�7.9) and Mini Mental Scale 26.1 (�2.7). Linear regression analysis showed that upper limb impairment and task complexity most effectively predicted setup time (51% as compared with 39%) (F(2,21) ¼ 12.782, adjusted R2 ¼ 0.506; p<.05). Conclusions: A model to predict setup time based on upper limb impairment and task complexity accounted for 51% of the variation in setup time. Further studies are required to test the model in real-world settings and to identify other contributing factors

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

It is not worth learning if it is not remembered: designing e-learning to increase memory

The collation, storage and retrieval of information are essential components of successful learning. Whether information is retained depends on a variety of factors, including how the information fits with an individual’s existing knowledge, the way in which information is presented, and its complexity. Some of these factors are under the direct control of the e-learning designers and developers. Investigating these factors and how they impact on memory is important and can enhance the quality of e-learning. Evidence from cognitive neuroscience suggests that information is stored in a semantically meaningful manner. It follows that e-learning technologies, which either mimic how knowledge is structured in the mind or which allow individuals to organise their own exploration of the information space, should facilitate learning and memory. However, the ability to freely explore an information space is also more taxing on an individual’s cognitive resources. Learners would need to expend cognitive resources remembering where they have been, as well as on deciding where to go next. These additional demands may impede learning, especially for more complex information. Most critical to investigate is the trade-off between the ability to build knowledge according to the learners’ cognitive structures and style (which is also more engaging), on the one hand; and the extra cognitive load associated with giving learners more control and information, on the other hand.In this study we investigated the relationship between information layout, complexity of information content, and memory. Seventy-six participants took part in the study. A third of them were presented with information that was laid out in a linear fashion: learners encountered the items of information in a fixed and constrained sequence. This layout provided a structure for remembering the presented information and minimised cognitive load. Another third of the participants were given full control; they could select the order in which they learned the different topics and could freely navigate between them. This layout increased cognitive load and eliminated context structure, but was also potentially more engaging and allowed for individual differences. The remaining third of participants received an intermediate version, giving some, but not total, control. All the participants studied eight topics, half of them were given relatively simple information on each topic, whereas the other half where given more complex information.The acquisition and retention of the learned material was assessed in all the experimental conditions. We found that constraining both the amount of information presented to the learners and the degree of navigational freedom they are given enhances information acquisition and retention. These factors are further discussed in terms of Cognitive Load Theory (CLT). Finally, the implication and application to e-learning design is considered

Chatbot trained on movie dialogue

A chatbot is a computer program that engages in written or spoken conversation with a human user. This project aims to investigate the possibility of training a chatbot in using movie dialogue in generating the response. Movie dialogue can be found in both movie scripts as well as subtitles, though using subtitles is much easier as they follow a special formatting. Using one subtitle as a response to each word found in the preceding subtitle, the implemented chatbot links together subtitles. The responses are stored in a frequency distribution table that maps each word to all responses found. Though the responses generated by the chatbot were not desirable, the responsese tmost often contained responses which would be more fitting. The result drawn from hisis that ,with further work and improvement,the chatbot could perform acceptabl

GIVING THE LEARNERS CONTROL OF NAVIGATION: COGNITIVE GAINS AND LOSSES

E-learning often involves exploration of the information space that is somewhat similar to the exploration of space in the real world. Initial paths taken in any environment (be it a physical, virtual, or any other type) will not only guide the discoveries of what the environment contains, but also formulate the underlying organising principles. The suggested route in an art gallery frequently presents artworks that are either chronological or conceptually tied together. Deviating from this –and taking a route of our own, if at all possible – might be either confusing or insightful. The structure of the information, and the control that the learners have in exploring it, plays a major role in determining mental representations and learning. In the virtual world these possibilities and degrees of freedom in navigation are less constrained than in the physical world, and thus, can be colossal. The question that arises is what are the gains and losses of allowing the learners to control their explorations in an information space? To investigate this, we designed three e-learning environments that differed in their navigational possibilities and structure, but all contained the same eight topics to be learned. The topics in the first environment (Linear) were in a strict order and the layout did not allow any alternation from this defined sequence of page visits. With this Linear structure, the learners had very little contro