1,028 research outputs found
DESIGN AND DEVELOPMENT OF 3D PRINTED MYOELECTRIC ROBOTIC EXOSKELETON FOR HAND REHABILITATION
The development of dynamic rehabilitation devices can be evaluated as a research fast-growing field. Indeed, robot-assisted therapy is an advanced new technology mainly in stroke rehabilitation. Although patients benefit from this enormous development of technology, including the presence of rehabilitation robots, the therapeutic field still suffering a lack in hand robotic rehabilitation devices. In this context, this work proposes a new design of a 3D printed hand exoskeleton for the stroke rehabilitation. Based on the EMG signals measured from the muscles responsible for the hand motion, the designed mechatronic system detects the intention of hand opening or hand closing from the stroked subject. Based on an embedded controller and five servomotors, the low cost robotic system is able to drive in real time three degrees of freedom (DOFs) for each finger. The real tests with stroked subjects showed that the designed hand exoskeleton architecture has a positive effect on the motion finger range and mainly in the hand ability to perform some simple tasks. The case studies showed a good recovery of the motor functions and consequently the developed system efficiency
Biosignal‐based human–machine interfaces for assistance and rehabilitation : a survey
As a definition, Human–Machine 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 biosignal‐based HMIs for assistance and rehabilitation to outline state‐of‐the‐art 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, full‐text), 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 ever‐growing 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 HMIs’ complex-ity, so their usefulness should be carefully evaluated for the specific application
Future bathroom: A study of user-centred design principles affecting usability, safety and satisfaction in bathrooms for people living with disabilities
Research and development work relating to assistive technology
2010-11 (Department of Health)
Presented to Parliament pursuant to Section 22 of the Chronically Sick and Disabled Persons Act 197
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
Rehabilitation Engineering
Population ageing has major consequences and implications in all areas of our daily life as well as other important aspects, such as economic growth, savings, investment and consumption, labour markets, pensions, property and care from one generation to another. Additionally, health and related care, family composition and life-style, housing and migration are also affected. Given the rapid increase in the aging of the population and the further increase that is expected in the coming years, an important problem that has to be faced is the corresponding increase in chronic illness, disabilities, and loss of functional independence endemic to the elderly (WHO 2008). For this reason, novel methods of rehabilitation and care management are urgently needed. This book covers many rehabilitation support systems and robots developed for upper limbs, lower limbs as well as visually impaired condition. Other than upper limbs, the lower limb research works are also discussed like motorized foot rest for electric powered wheelchair and standing assistance device
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