title: Rehabilitation of gait after stroke: a review towards a top-down approach.
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.
authors.affiliation: Instituto de Biomecánica de Valencia, Universitat Politécnica de Valencia, Valencia, Spain. juanma.belda@ibv.upv.es
authors.forename: Juan-Manuel
authors.initials: JM
authors.lastname: Belda-Lois
authors.forename: Silvia
authors.initials: S
authors.lastname: Mena-del Horno
authors.forename: Ignacio
authors.initials: I
authors.lastname: Bermejo-Bosch
authors.forename: Juan C
authors.initials: JC
authors.lastname: Moreno
authors.forename: José L
authors.initials: JL
authors.lastname: Pons
authors.forename: Dario
authors.initials: D
authors.lastname: Farina
authors.forename: Marco
authors.initials: M
authors.lastname: Iosa
authors.forename: Marco
authors.initials: M
authors.lastname: Molinari
authors.forename: Federica
authors.initials: F
authors.lastname: Tamburella
authors.forename: Ander
authors.initials: A
authors.lastname: Ramos
authors.forename: Andrea
authors.initials: A
authors.lastname: Caria
authors.forename: Teodoro
authors.initials: T
authors.lastname: Solis-Escalante
authors.forename: Clemens
authors.initials: C
authors.lastname: Brunner
authors.forename: Massimiliano
authors.initials: M
authors.lastname: Rea
mesh_terms: D003627:Data Interpretation, Statistical; D004558:Electric Stimulation; D004569:Electroencephalography; D005684:Gait / Q000502:physiology*; D006801:Humans; D007858:Learning; D009068:Movement; D009482:Neurophysiology; D012371:Robotics; D019265:Spectroscopy, Near-Infrared; D000071939:Stroke Rehabilitation; D014584:User-Computer Interface