Stroke rehabilitation has undergone a revolution over the last three decades. Cohort studies have consistently reinforced the importance of post-stroke rehabilitation to stimulate recovery, but the concepts of empirical methods originally proposed by therapists to rehabilitate these patients have not withstood clinical analysis. Functional neuroimaging and animal models have unveiled the mechanisms underlying functional recovery and helped teams understand its limitations and improvement modalities. These neuroscience discoveries constitute the grounds needed to understand the emergence of new technologies: robotics and virtual reality. The objective of this review of the literature was to select key works in this field to better understand current therapeutic possibilities.

Stroke patients have impaired postural balance that increases the risk of falls and impairs their mobility. Assessment of postural balance is commonly carried out by recording centre of pressure (CoP) displacements, but the lack of data concerning reliability of these measures compromises their interpretation. The purpose of this study was to investigate the between-day reliability of six CoP-based variables, in order to provide i) reliability data for monitoring postural sway and weight-bearing asymmetry of stroke patients in clinical practice and ii) consistent assessment method of measurement error for applications in physical medicine and rehabilitation.

Functional magnetic resonance imaging (fMRI) is a widely used technique for assessing brain function in both healthy and pathological populations. Some factors, such as motion, physiological noise and lesion presence, can contribute to signal change and confound the fMRI data, but fMRI data processing techniques have been developed to correct for these confounding effects. Fifteen spastic subacute stroke patients underwent fMRI while performing a highly controlled task (i.e. passive extension of their affected and unaffected wrists). We investigated the impact on activation maps of lesion masking during preprocessing and first- and second-level analyses, and of adding wrist extension amplitudes and physiological data as regressors using the Statistical Parametric Mapping toolbox (SPM12).