762 research outputs found
Neuroplastic Changes Following Brain Ischemia and their Contribution to Stroke Recovery: Novel Approaches in Neurorehabilitation
Ischemic damage to the brain triggers substantial reorganization of spared areas and pathways, which is associated with limited, spontaneous restoration of function. A better understanding of this plastic remodeling is crucial to develop more effective strategies for stroke rehabilitation. In this review article, we discuss advances in the comprehension of post-stroke network reorganization in patients and animal models. We first focus on rodent studies that have shed light on the mechanisms underlying neuronal remodeling in the perilesional area and contralesional hemisphere after motor cortex infarcts. Analysis of electrophysiological data has demonstrated brain-wide alterations in functional connectivity in both hemispheres, well beyond the infarcted area. We then illustrate the potential use of non-invasive brain stimulation (NIBS) techniques to boost recovery. We finally discuss rehabilitative protocols based on robotic devices as a tool to promote endogenous plasticity and functional restoration
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 usersâ motor residual capabilities,
while the associative term denotes a precise pairing between the usersâ 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 usersâ
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 AutomĂĄticaPresidente: RamĂłn Ceres Ruiz.- Secretario: Luis Enrique Moreno Lorente.- Vocal: Antonio Olivier
Robotic design and modelling of medical lower extremity exoskeletons
This study aims to explain the development of the robotic Lower Extremity Exoskeleton (LEE) systems between 1960
and 2019 in chronological order. The scans performed in the exoskeleton systemâs design have shown that a modeling
program, such as AnyBody, and OpenSim, should be used first to observe the design and software animation, followed
by the mechanical development of the system using sensors and motors. Also, the use of OpenSim and AnyBody
musculoskeletal system software has been proven to play an essential role in designing the human-exoskeleton by
eliminating the high costs and risks of the mechanical designs. Furthermore, these modeling systems can enable rapid
optimization of the LEE design by detecting the forces and torques falling on the human muscles
Optimizing User Integration for Individualized Rehabilitation
User integration with assistive devices or rehabilitation protocols to improve movement function is a key principle to consider for developers to truly optimize performance gains. Better integration may entail customizing operation of devices and training programs according to several user characteristics during execution of functional tasks. These characteristics may be physical dimensions, residual capabilities, restored sensory feedback, cognitive perception, or stereotypical actions
Post-stroke Rehabilitation of Severe Upper Limb Paresis in Germany â Toward Long-Term Treatment With Brain-Computer Interfaces
Severe upper limb paresis can represent an immense burden for stroke survivors. Given the rising prevalence of stroke, restoration of severe upper limb motor impairment remains a major challenge for rehabilitation medicine because effective treatment strategies are lacking. Commonly applied interventions in Germany, such as mirror therapy and impairment-oriented training, are limited in efficacy, demanding for new strategies to be found. By translating brain signals into control commands of external devices, brain-computer interfaces (BCIs) and brain-machine interfaces (BMIs) represent promising, neurotechnology-based alternatives for stroke patients with highly restricted arm and hand function. In this mini-review, we outline perspectives on how BCI-based therapy can be integrated into the different stages of neurorehabilitation in Germany to meet a long-term treatment approach: We found that it is most appropriate to start therapy with BCI-based neurofeedback immediately after early rehabilitation. BCI-driven functional electrical stimulation (FES) and BMI robotic therapy are well suited for subsequent post hospital curative treatment in the subacute stage. BCI-based hand exoskeleton training can be continued within outpatient occupational therapy to further improve hand function and address motivational issues in chronic stroke patients. Once the rehabilitation potential is exhausted, BCI technology can be used to drive assistive devices to compensate for impaired function. However, there are several challenges yet to overcome before such long-term treatment strategies can be implemented within broad clinical application: 1. developing reliable BCI systems with better usability; 2. conducting more research to improve BCI training paradigms and 3. establishing reliable methods to identify suitable patients
Biosignalâbased humanâmachine interfaces for assistance and rehabilitation : a survey
As a definition, HumanâMachine Interface (HMI) enables a person to interact with a device. Starting from elementary equipment, the recent development of novel techniques and unobtrusive devices for biosignals monitoring paved the way for a new class of HMIs, which take such biosignals as inputs to control various applications. The current survey aims to review the large literature of the last two decades regarding biosignalâbased HMIs for assistance and rehabilitation to outline stateâofâtheâart and identify emerging technologies and potential future research trends. PubMed and other databases were surveyed by using specific keywords. The found studies were further screened in three levels (title, abstract, fullâtext), and eventually, 144 journal papers and 37 conference papers were included. Four macrocategories were considered to classify the different biosignals used for HMI control: biopotential, muscle mechanical motion, body motion, and their combinations (hybrid systems). The HMIs were also classified according to their target application by considering six categories: prosthetic control, robotic control, virtual reality control, gesture recognition, communication, and smart environment control. An everâgrowing number of publications has been observed over the last years. Most of the studies (about 67%) pertain to the assistive field, while 20% relate to rehabilitation and 13% to assistance and rehabilitation. A moderate increase can be observed in studies focusing on robotic control, prosthetic control, and gesture recognition in the last decade. In contrast, studies on the other targets experienced only a small increase. Biopotentials are no longer the leading control signals, and the use of muscle mechanical motion signals has experienced a considerable rise, especially in prosthetic control. Hybrid technologies are promising, as they could lead to higher performances. However, they also increase HMIsâ complex-ity, so their usefulness should be carefully evaluated for the specific application
Physical Diagnosis and Rehabilitation Technologies
The book focuses on the diagnosis, evaluation, and assistance of gait disorders; all the papers have been contributed by research groups related to assistive robotics, instrumentations, and augmentative devices
Enhancement of Robot-Assisted Rehabilitation Outcomes of Post-Stroke Patients Using Movement-Related Cortical Potential
Post-stroke rehabilitation is essential for stroke survivors to help them regain independence and to improve their quality of life. Among various rehabilitation strategies, robot-assisted rehabilitation is an efficient method that is utilized more and more in clinical practice for motor recovery of post-stroke patients. However, excessive assistance from robotic devices during rehabilitation sessions can make patients perform motor training passively with minimal outcome. Towards the development of an efficient rehabilitation strategy, it is necessary to ensure the active participation of subjects during training sessions. This thesis uses the Electroencephalography (EEG) signal to extract the Movement-Related Cortical Potential (MRCP) pattern to be used as an indicator of the active engagement of stroke patients during rehabilitation training sessions. The MRCP pattern is also utilized in designing an adaptive rehabilitation training strategy that maximizes patientsâ engagement.
This project focuses on the hand motor recovery of post-stroke patients using the AMADEO rehabilitation device (Tyromotion GmbH, Austria). AMADEO is specifically developed for patients with fingers and hand motor deficits.
The variations in brain activity are analyzed by extracting the MRCP pattern from the acquired EEG data during training sessions. Whereas, physical improvement in hand motor abilities is determined by two methods. One is clinical tests namely Fugl-Meyer Assessment (FMA) and Motor Assessment Scale (MAS) which include FMA-wrist, FMA-hand, MAS-hand movements, and MAS-advanced hand movementsâ tests. The other method is the measurement of hand-kinematic parameters using the AMADEO assessment tool which contains hand strength measurements during flexion (force-flexion), and extension (force-extension), and Hand Range of Movement (HROM)
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