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      Rehabilitation of gait after stroke: a review towards a top-down approach

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          Abstract

          This document provides a review of the techniques and therapies used in gait rehabilitation after stroke. It also examines the possible benefits of including assistive robotic devices and brain-computer interfaces in this field, according to a top-down approach, in which rehabilitation is driven by neural plasticity.

          The methods reviewed comprise classical gait rehabilitation techniques (neurophysiological and motor learning approaches), functional electrical stimulation (FES), robotic devices, and brain-computer interfaces (BCI).

          From the analysis of these approaches, we can draw the following conclusions. Regarding classical rehabilitation techniques, there is insufficient evidence to state that a particular approach is more effective in promoting gait recovery than other. Combination of different rehabilitation strategies seems to be more effective than over-ground gait training alone. Robotic devices need further research to show their suitability for walking training and their effects on over-ground gait. The use of FES combined with different walking retraining strategies has shown to result in improvements in hemiplegic gait. Reports on non-invasive BCIs for stroke recovery are limited to the rehabilitation of upper limbs; however, some works suggest that there might be a common mechanism which influences upper and lower limb recovery simultaneously, independently of the limb chosen for the rehabilitation therapy. Functional near infrared spectroscopy (fNIRS) enables researchers to detect signals from specific regions of the cortex during performance of motor activities for the development of future BCIs. Future research would make possible to analyze the impact of rehabilitation on brain plasticity, in order to adapt treatment resources to meet the needs of each patient and to optimize the recovery process.

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          Author and article information

          Journal
          J Neuroeng Rehabil
          Journal of NeuroEngineering and Rehabilitation
          BioMed Central
          1743-0003
          2011
          13 December 2011
          : 8
          : 66
          Affiliations
          [1 ]Instituto de Biomecánica de Valencia, Universitat Politécnica de Valencia, Camino de Vera, s/n ed. 9C, E46022 Valencia, Spain
          [2 ]Grupo de Tecnología Sanitaria del IBV, CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN). Valencia, Spain
          [3 ]Bioengineering Group, Center for Automation and Robotics, Spanish National Research Council (CSIC). Madrid, Spain
          [4 ]Department of Neurorehabilitation Engineering, Bernstein Center for Computational Neuroscience University Medical Center Göttingen Georg-August University. Göttingen, Germany
          [5 ]Fondazione Santa Lucia. Roma, Italy
          [6 ]University of Tübingen. Tübingen, Germany
          [7 ]TECNALIA Research and Innovation Germany. Tübingen, Germany
          [8 ]Graz University of Technology. Austria
          Article
          1743-0003-8-66
          10.1186/1743-0003-8-66
          3261106
          22165907
          8a936b2d-1d3b-4fb1-bbae-7e60a92b73db
          Copyright ©2011 Belda-Lois et al; licensee BioMed Central Ltd.

          This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

          History
          : 4 April 2011
          : 13 December 2011
          Categories
          Review

          Neurosciences
          Neurosciences

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