2,042 research outputs found
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
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
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
The re-education of upper limb movement post stroke using iterative learning control mediated by electrical stimulation
An inability to perform tasks involving reaching is a common problem following stroke. Evidence supports the use of robotic therapy and electrical stimulation (ES) to reduce upper limb impairments following stroke, but current systems may not encourage maximal voluntary contribution from the participant. This study developed and tested iterative learning control (ILC) algorithms mediated by ES, using a purpose designed robotic workstation, for upper limb rehabilitation post stroke. Surface electromyography (EMG) which may be related to impaired performance and function was used to investigate seven shoulder and elbow muscle activation patterns in eight neurologically intact and five chronic stroke participants during nine tracking tasks. The participants’ forearm was supported using a hinged arm-holder, which constrained their hand to move in a two dimensional horizontal plane.Outcome measures taken prior to and after an intervention consisted of the Fugl-Meyer Assessment (FMA) and the Action Research Arm Test (ARAT), isometric force and error tracking. The intervention for stroke participants consisted of eighteen sessions in which a similar range of tracking tasks were performed with the addition of responsive electrical stimulation to their triceps muscle. A question set was developed to understand participants’ perceptions of the ILC system. Statistically significant improvements were measured (p?0.05) in: FMA motor score, unassisted tracking, and in isometric force. Statistically significant differences in muscle activation patterns were observed between stroke and neurologically intact participants for timing, amplitude and coactivation patterns. After the intervention significant changes were observed in many of these towards neurologically intact ranges. The robot–assisted therapy was well accepted and tolerated by the stroke participants. This study has demonstrated the feasibility of using ILC mediated by ES for upper limb stroke rehabilitation in the treatment of stroke patients with upper limb hemiplegia
Development of a hybrid robotic system based on an adaptive and associative assistance for rehabilitation of reaching movement after stroke
Stroke causes irreversible neurological damage. Depending on the location and the size of
this brain injury, different body functions could result affected. One of the most common
consequences is motor impairments. The level of motor impairment affectation varies between
post-stroke subjects, but often, it hampers the execution of most activities of daily living.
Consequently, the quality of life of the stroke population is severely decreased.
The rehabilitation of the upper-limb motor functions has gained special attention in the
scientific community due the poor reported prognosis of post-stroke patients for recovering
normal upper-extremity function after standard rehabilitation therapy. Driven by the advance
of technology and the design of new rehabilitation methods, the use of robot devices,
functional electrical stimulation and brain-computer interfaces as a neuromodulation system
is proposed as a novel and promising rehabilitation tools. Although the uses of these technologies
present potential benefits with respect to standard rehabilitation methods, there still
are some milestones to be addressed for the consolidation of these methods and techniques
in clinical settings.
Mentioned evidences reflect the motivation for this dissertation. This thesis presents the
development and validation of a hybrid robotic system based on an adaptive and associative
assistance for rehabilitation of reaching movements in post-stroke subjects. The hybrid
concept refers the combined use of robotic devices with functional electrical stimulation.
Adaptive feature states a tailored assistance according to the users’ motor residual capabilities,
while the associative term denotes a precise pairing between the users’ motor intent
and the peripheral hybrid assistance. The development of the hybrid platform comprised the
following tasks:
1. The identification of the current challenges for hybrid robotic system, considering twofold
perspectives: technological and clinical. The hybrid systems submitted in literature
were critically reviewed for such purpose. These identified features will lead the
subsequent development and method framed in this work.
2. The development and validation of a hybrid robotic system, combining a mechanical
exoskeleton with functional electrical stimulation to assist the execution of functional
reaching movements. Several subsystems are integrated within the hybrid platform,
which interact each other to cooperatively complement the rehabilitation task. Complementary,
the implementation of a controller based on functional electrical stimulation
to dynamically adjust the level of assistance is addressed. The controller is conceived to
tackle one of the main limitations when using electrical stimulation, i.e. the highly nonlinear
and time-varying muscle response. An experimental procedure was conducted
with healthy and post-stroke patients to corroborate the technical feasibility and the
usability evaluation of the system.
3. The implementation of an associative strategy within the hybrid platform. Three different
strategies based on electroencephalography and electromyography signals were
analytically compared. The main idea is to provide a precise temporal association between
the hybrid assistance delivered at the periphery (arm muscles) and the users’
own intention to move and to configure a feasible clinical setup to be use in real rehabilitation
scenarios.
4. Carry out a comprehensive pilot clinical intervention considering a small cohort of
patient with post-stroke patients to evaluate the different proposed concepts and assess
the feasibility of using the hybrid system in rehabilitation settings.
In summary, the works here presented prove the feasibility of using the hybrid robotic system
as a rehabilitative tool with post-stroke subjects. Moreover, it is demonstrated the adaptive
controller is able to adjust the level of assistance to achieve successful tracking movement
with the affected arm. Remarkably, the accurate association in time between motor cortex
activation, represented through the motor-related cortical potential measured with electroencephalography,
and the supplied hybrid assistance during the execution of functional (multidegree
of freedom) reaching movement facilitate distributed cortical plasticity. These results
encourage the validation of the overall hybrid concept in a large clinical trial including an
increased number of patients with a control group, in order to achieve more robust clinical
results and confirm the presented herein.Programa Oficial de Doctorado en IngenierĂa ElĂ©ctrica, ElectrĂłnica y AutomáticaPresidente: RamĂłn Ceres Ruiz.- Secretario: Luis Enrique Moreno Lorente.- Vocal: Antonio Olivier
Upper limb electrical stimulation using input-output linearization and iterative learning control
A control scheme is developed for multi-joint upper limb reference tracking using functional electrical stimulation (FES). In accordance with the needs of stroke rehabilitation, FES is applied to a reduced set of muscles in the arm and shoulder, with support against gravity provided by a passive exoskeletal mechanism. The approach fuses input-output linearization with iterative learning control (ILC), one of the few techniques to have been applied in clinical treatment trials with patients. This powerful hybrid control structure hence extends performance and scope of clinically proven technology for widespread application in rehabilitation robotic and FES domains. In addition to simplifying tracking and convergence properties of the stimulated joints, the framework enables conditions for the stability of unstimulated joints to be derived for the first time. Experimental results confirm tracking performance of the stimulated joints, together with unstimulated joint stability
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