5,067 research outputs found
Rehabilitative devices for a top-down approach
In recent years, neurorehabilitation has moved from a "bottom-up" to a "top down" approach. This change has also involved the technological devices developed for motor and cognitive rehabilitation. It implies that during a task or during therapeutic exercises, new "top-down" approaches are being used to stimulate the brain in a more direct way to elicit plasticity-mediated motor re-learning. This is opposed to "Bottom up" approaches, which act at the physical level and attempt to bring about changes at the level of the central neural system. Areas covered: In the present unsystematic review, we present the most promising innovative technological devices that can effectively support rehabilitation based on a top-down approach, according to the most recent neuroscientific and neurocognitive findings. In particular, we explore if and how the use of new technological devices comprising serious exergames, virtual reality, robots, brain computer interfaces, rhythmic music and biofeedback devices might provide a top-down based approach. Expert commentary: Motor and cognitive systems are strongly harnessed in humans and thus cannot be separated in neurorehabilitation. Recently developed technologies in motor-cognitive rehabilitation might have a greater positive effect than conventional therapies
Review of control strategies for robotic movement training after neurologic injury
There is increasing interest in using robotic devices to assist in movement training following neurologic injuries such as stroke and spinal cord injury. This paper reviews control strategies for robotic therapy devices. Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching. The greatest amount of work has been done on developing assistive strategies, and thus the majority of this review summarizes techniques for implementing assistive strategies, including impedance-, counterbalance-, and EMG- based controllers, as well as adaptive controllers that modify control parameters based on ongoing participant performance. Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others. It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training. In future research, there is a need for head-to-head comparison of control algorithms in randomized, controlled clinical trials, and for improved models of human motor recovery to provide a more rational framework for designing robotic therapy control strategies
Diseño de entornos de realidad virtual aplicables a sistemas de robótica asistencial: un análisis literario
Virtual Reality (VR) environments can be applied to assistive robotics to improve the effectiveness and the user experience perception in the rehabilitation process due to its innovative nature, getting to entertain patients while they recover their motor functions. This literature review pretends to analyze some design principles of VR environments developed for upper limb rehabilitation processes. The idea is to identify features related to peripheral and central nervous systems, types of information included as feedback to increase the user's levels of immersion having a positive impact on the user's performance and experience during the treatment. A total of 32 articles published in Scopus, IEEE, PubMed, and Web of Science in the last four years were reviewed. We present the article selection process, the division by concepts presented previously, and the guidelines that can be considered for the design of VR environments applicable to assistive robots for upper limbs rehabilitation processes.Los entornos de Realidad Virtual (RV) aplicables a sistemas de robótica asistencial pueden ser diseñados de manera que mejoren la efectividad y la experiencia de usuario de los procesos de rehabilitación debido a su naturaleza novedosa, logrando entretener a los pacientes mientras recuperan sus funciones motoras. Esta revisión literaria pretende analizar los criterios de diseño de entornos de RV utilizados en procesos de rehabilitación de miembro superior, identificando las características de entornos para rehabilitación de problemas asociados el sistema nervioso central y periféricos, los tipos de información que se realimenta al usuario para beneficiar los niveles de inmersión y su impacto en términos del desempeño y la experiencia del usuario en tratamiento. Un total de 32 artículos publicados en revistas indexadas de Scopus, IEEE, PubMed y Web of Science en los últimos cuatro años fueron revisados. Se presenta el proceso de selección de artículos, la división por las temáticas presentadas anteriormente y los lineamientos generales que pueden ser considerados para el diseño de entornos de RV aplicables a robots asistenciales en procesos de rehabilitación de miembro superior
Voltage stability analysis of load buses in electric power system using adaptive neuro-fuzzy inference system (anfis) and probabilistic neural network (pnn)
This paper presents the application of neural networks for analysing voltage stability of load buses in electric
power system. Voltage stability margin (VSM) and load power margin (LPM) are used as the indicators for analysing
voltage stability. The neural networks used in this research are divided into two types. The first type is using the neural
network to predict the values of VSM and LPM. Multilayer perceptron back propagation (MLPBP) neural network and
adaptive neuro-fuzzy inference system (ANFIS) will be used. The second type is to classify the values of VSM and LPM
using the probabilistic neural network (PNN). The IEEE 30-bus system has been chosen as the reference electrical power
system. All of the neural network-based models used in this research is developed using MATLAB
In-home and remote use of robotic body surrogates by people with profound motor deficits
By controlling robots comparable to the human body, people with profound
motor deficits could potentially perform a variety of physical tasks for
themselves, improving their quality of life. The extent to which this is
achievable has been unclear due to the lack of suitable interfaces by which to
control robotic body surrogates and a dearth of studies involving substantial
numbers of people with profound motor deficits. We developed a novel, web-based
augmented reality interface that enables people with profound motor deficits to
remotely control a PR2 mobile manipulator from Willow Garage, which is a
human-scale, wheeled robot with two arms. We then conducted two studies to
investigate the use of robotic body surrogates. In the first study, 15 novice
users with profound motor deficits from across the United States controlled a
PR2 in Atlanta, GA to perform a modified Action Research Arm Test (ARAT) and a
simulated self-care task. Participants achieved clinically meaningful
improvements on the ARAT and 12 of 15 participants (80%) successfully completed
the simulated self-care task. Participants agreed that the robotic system was
easy to use, was useful, and would provide a meaningful improvement in their
lives. In the second study, one expert user with profound motor deficits had
free use of a PR2 in his home for seven days. He performed a variety of
self-care and household tasks, and also used the robot in novel ways. Taking
both studies together, our results suggest that people with profound motor
deficits can improve their quality of life using robotic body surrogates, and
that they can gain benefit with only low-level robot autonomy and without
invasive interfaces. However, methods to reduce the rate of errors and increase
operational speed merit further investigation.Comment: 43 Pages, 13 Figure
Flexible Virtual Reality System for Neurorehabilitation and Quality of Life Improvement
As life expectancy is mostly increasing, the incidence of many neurological
disorders is also constantly growing. For improving the physical functions
affected by a neurological disorder, rehabilitation procedures are mandatory,
and they must be performed regularly. Unfortunately, neurorehabilitation
procedures have disadvantages in terms of costs, accessibility and a lack of
therapists. This paper presents Immersive Neurorehabilitation Exercises Using
Virtual Reality (INREX-VR), our innovative immersive neurorehabilitation system
using virtual reality. The system is based on a thorough research methodology
and is able to capture real-time user movements and evaluate joint mobility for
both upper and lower limbs, record training sessions and save electromyography
data. The use of the first-person perspective increases immersion, and the
joint range of motion is calculated with the help of both the HTC Vive system
and inverse kinematics principles applied on skeleton rigs. Tutorial exercises
are demonstrated by a virtual therapist, as they were recorded with real-life
physicians, and sessions can be monitored and configured through tele-medicine.
Complex movements are practiced in gamified settings, encouraging
self-improvement and competition. Finally, we proposed a training plan and
preliminary tests which show promising results in terms of accuracy and user
feedback. As future developments, we plan to improve the system's accuracy and
investigate a wireless alternative based on neural networks.Comment: 47 pages, 20 figures, 17 tables (including annexes), part of the MDPI
Sesnsors "Special Issue Smart Sensors and Measurements Methods for Quality of
Life and Ambient Assisted Living
Markerless assisted rehabilitation system
The project focuses on the use of modern technology to analyze human movement. This analysis turns out to be useful aid for physicians in rehabilitation of patients with limb injuries. This method is more precise than simple observation of the patient through the organ of sight. The proposed system allows markerless determination of deviations between the selected bones and joints, and as a result do not require specialized and expensive equipment. The implemented application presents instructional animation of the exercises and verify the correctness of its performance in real time. The equipment that meets the requirements of the project is the Microsoft Kinect, which is nowadays widely used in the medical field
Upper-limb Kinematic Analysis and Artificial Intelligent Techniques for Neurorehabilitation and Assistive Environments
Stroke, one of the leading causes of death and disability around the
world, usually affects the motor cortex causing weakness or paralysis
in the limbs of one side of the body. Research efforts in neurorehabilitation
technology have focused on the development of robotic devices to
restore motor and cognitive function in impaired individuals, having
the potential to deliver high-intensity and motivating therapy.
End-effector-based devices have become an usual tool in the upper-
limb neurorehabilitation due to the ease of adapting to patients.
However, they are unable to measure the joint movements during
the exercise. Thus, the first part of this thesis is focused on the development
of a kinematic reconstruction algorithm that can be used
in a real rehabilitation environment, without disturbing the normal
patient-clinician interaction. On the basis of the algorithm found in
the literature that presents some instabilities, a new algorithm is developed.
The proposed algorithm is the first one able to online estimate
not only the upper-limb joints, but also the trunk compensation using
only two non-invasive wearable devices, placed onto the shoulder and
upper arm of the patient. This new tool will allow the therapist to perform
a comprehensive assessment combining the range of movement
with clinical assessment scales.
Knowing that the intensity of the therapy improves the outcomes of
neurorehabilitation, a ‘self-managed’ rehabilitation system can allow
the patients to continue the rehabilitation at home. This thesis proposes
a system to online measure a set of upper-limb rehabilitation gestures,
and intelligently evaluates the quality of the exercise performed by
the patients. The assessment is performed through the study of the
performed movement as a whole as well as evaluating each joint
independently. The first results are promising and suggest that this
system can became a a new tool to complement the clinical therapy at
home and improve the rehabilitation outcomes.
Finally, severe motor condition can remain after rehabilitation process.
Thus, a technology solution for these patients and people with
severe motor disabilities is proposed. An intelligent environmental
control interface is developed with the ability to adapt its scan control
to the residual capabilities of the user. Furthermore, the system estimates
the intention of the user from the environmental information and the behavior of the user, helping in the navigation through the
interface, improving its independence at home.El accidente cerebrovascular o ictus es una de las causas principales
de muerte y discapacidad a nivel mundial. Normalmente afecta a la
corteza motora causando debilidad o parálisis en las articulaciones del
mismo lado del cuerpo. Los esfuerzos de investigación dentro de la
tecnología de neurorehabilitación se han centrado en el desarrollo de
dispositivos robóticos para restaurar las funciones motoras y cognitivas
en las personas con esta discapacidad, teniendo un gran potencial
para ofrecer una terapia de alta intensidad y motivadora.
Los dispositivos basados en efector final se han convertido en una
herramienta habitual en la neurorehabilitación de miembro superior
ya que es muy sencillo adaptarlo a los pacientes. Sin embargo, éstos
no son capaces de medir los movimientos articulares durante la realización
del ejercicio. Por tanto, la primera parte de esta tesis se centra
en el desarrollo de un algoritmo de reconstrucción cinemática que
pueda ser usado en un entorno de rehabilitación real, sin perjudicar a
la interacción normal entre el paciente y el clínico. Partiendo de la base
que propone el algoritmo encontrado en la literatura, el cual presenta
algunas inestabilidades, se ha desarrollado un nuevo algoritmo. El
algoritmo propuesto es el primero capaz de estimar en tiempo real
no sólo las articulaciones del miembro superior, sino también la compensación
del tronco usando solamente dos dispositivos no invasivos
y portátiles, colocados sobre el hombro y el brazo del paciente. Esta
nueva herramienta permite al terapeuta realizar una valoración más
exhaustiva combinando el rango de movimiento con las escalas de
valoración clínicas.
Sabiendo que la intensidad de la terapia mejora los resultados de la
recuperación del ictus, un sistema de rehabilitación ‘auto-gestionado’
permite a los pacientes continuar con la rehabilitación en casa. Esta
tesis propone un sistema para medir en tiempo real un conjunto de
gestos de miembro superior y evaluar de manera inteligente la calidad
del ejercicio realizado por el paciente. La valoración se hace a través del
estudio del movimiento ejecutado en su conjunto, así como evaluando
cada articulación independientemente. Los primeros resultados son
prometedores y apuntan a que este sistema puede convertirse en una
nueva herramienta para complementar la terapia clínica en casa y
mejorar los resultados de la rehabilitación. Finalmente, después del proceso de rehabilitación pueden quedar
secuelas motoras graves. Por este motivo, se propone una solución
tecnológica para estas personas y para personas con discapacidades
motoras severas. Así, se ha desarrollado una interfaz de control de
entorno inteligente capaz de adaptar su control a las capacidades
residuales del usuario. Además, el sistema estima la intención del
usuario a partir de la información del entorno y el comportamiento del
usuario, ayudando en la navegación a través de la interfaz, mejorando
su independencia en el hogar
Effectiveness of intensive physiotherapy for gait improvement in stroke: systematic review
Introduction: Stroke is one of the leading causes of functional disability worldwide. Approximately 80% of post-stroke subjects have motor changes. Improvement of gait pattern is one of the main objectives of physiotherapists intervention in these cases. The real challenge in the recovery of gait after stroke is to understand how the remaining neural networks can be modified, to be able to provide response strategies that compensate for the function of the affected structures. There is evidence that intensive training, including physiotherapy, positively influences neuroplasticity, improving mobility, pattern and gait velocity in post-stroke recovery. Objectives: Review and analyze in a systematic way the experimental studies (RCT) that evaluate the effects of Intensive Physiotherapy on gait improvement in poststroke subjects. Methodology: Were only included all RCT performed in humans, without any specific age, that had a clinical diagnosis of stroke at any stage of evolution, with sensorimotor deficits and functional gait changes. The databases used were: Pubmed, PEDro (Physiotherapy Evidence Database) and CENTRAL (Cochrane Center Register of Controlled Trials). Results: After the application of the criteria, there were 4 final studies that were included in the systematic review. 3 of the studies obtained a score of 8 on the PEDro scale and 1 obtained a score of 4. The fact that there is clinical and methodological heterogeneity in the studies evaluated, supports the realization of the current systematic narrative review, without meta-analysis. Discussion: Although the results obtained in the 4 studies are promising, it is important to note that the significant improvements that have been found, should be carefully considered since pilot studies with small samples, such as these, are not designed to test differences between groups, in terms of the effectiveness of the intervention applied. Conclusion: Intensive Physiotherapy seems to be safe and applicable in post-stroke subjects and there are indications that it is effective in improving gait, namely speed, travelled distance and spatiotemporal parameters. However, there is a need to develop more RCTs with larger samples and that evaluate the longterm resultsN/
Interactive IIoT-Based 5DOF Robotic Arm for Upper Limb Telerehabilitation
Significant advancements in contemporary telemedicine applications enforce the demand for effective and intuitive telerehabilitation tools. Telerehabilitation can minimize the distance, travel burden, and costs between rehabilitative patients and therapists. This research introduces an interactive novel telerehabilitation system that integrates the Industrial Internet of Things (IIoT) platform with a robotic manipulator named xARm-5, aiming to deliver rehabilitation therapies to individuals with upper limb dysfunctions. With the proposed system, a therapist can provide upper limb rehab exercises remotely using an augmented reality (AR) user interface (UI) developed using Vuforia Studio, which transmits bidirectional data through the IIoT platform. The proposed system has a stable communication architecture and low teleoperation latency. Experimental results revealed that with the developed telerehabilitation framework, the xArm-5 could be teleoperated from the developed AR platform and/or use a joystick to provide standard upper limb rehab exercises. Besides, with the designed AR-based UI, a therapist can monitor rehab/robot trajectories along with the AR digital twin of the robot, ensuring that the robot is providing passive therapy for shoulder and elbow movements
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