This work deals with neural network (NN)-based gait pattern adaptation algorithms for an active lower-limb orthosis. Stable trajectories with different walking speeds are generated during an optimization process considering the zero-moment point (ZMP) criterion and the inverse dynamic of the orthosis-patient model. Additionally, a set of NNs is used to decrease the time-consuming analytical computation of the model and ZMP. The first NN approximates the inverse dynamics including the ZMP computation, while the second NN works in the optimization procedure, giving an adapted desired trajectory according to orthosis-patient interaction. This trajectory adaptation is added directly to the trajectory generator, also reproduced by a set of NNs. With this strategy, it is possible to adapt the trajectory during the walking cycle in an on-line procedure, instead of changing the trajectory parameter after each step. The dynamic model of the actual exoskeleton, with interaction forces included, is used to generate simulation results. Also, an experimental test is performed with an active ankle-foot orthosis, where the dynamic variables of this joint are replaced in the simulator by actual values provided by the device. It is shown that the final adapted trajectory follows the patient intention of increasing the walking speed, so changing the gait pattern.

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The primary motor cortex is a critical node in the network of brain regions responsible for voluntary motor behavior. It has been less appreciated, however, that the motor cortex exhibits sensory responses in a variety of modalities including vision and somatosensation. We review current work that emphasizes the heterogeneity in sensorimotor responses in the motor cortex and focus on its implications for cortical control of movement as well as for brain-machine interface development.

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This paper illustrates the mechanical structure’s spherical motion, kinematic matrices and achievable workspace of an exoskeleton upper limb device. The purpose of this paper is to assist individuals that have lost their upper limb motor functions by creating an exoskeleton device that does not require an external support; but still provides a large workspace. This allows for movement according to the Activities of Daily Living (ADL).

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Current health services are struggling to provide optimal rehabilitation therapy to victims of stroke. This has motivated researchers to explore the use of robotic devices to provide rehabilitation therapy for strokepatients. This paper reviews the recent progress of upper limb exoskeleton robots for rehabilitation treatment of patients with neuromuscular disorders. Firstly, a brief introduction to rehabilitation robots will be given along with examples of existing commercial devices. The advancements in upper limb exoskeleton technology and the fundamental challenges in developing these devices are described. Potential areas for future research are discussed.

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Currently, over a billion people including children (or about 15% of the world’s population) are estimated to be living with disability. The lack of support services can make handicapped people overly dependent on their families, which prevents from being economically active and socially included. The Internet of Things can offer people with disabilities the assistance and support they need to achieve a good quality of life and allows them to participate in the social and economic life. In this paper, an overview of the Internet of Things for people with disabilities is provided. For this purpose, the proposed architecture of the Internet of Things is introduced. Different application scenarios are considered in order to illustrate the interaction of the components of the Internet of Things. Critical challenges have been identified and addressed.

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