Posts Tagged Neurorehabilitation

[ARTICLE] The Promotoer, a brain-computer interface-assisted intervention to promote upper limb functional motor recovery after stroke: a study protocol for a randomized controlled trial to test early and long-term efficacy and to identify determinants of response – Full Text



Stroke is a leading cause of long-term disability. Cost-effective post-stroke rehabilitation programs for upper limb are critically needed. Brain-Computer Interfaces (BCIs) which enable the modulation of Electroencephalography (EEG) sensorimotor rhythms are promising tools to promote post-stroke recovery of upper limb motor function. The “Promotoer” study intends to boost the application of the EEG-based BCIs in clinical practice providing evidence for a short/long-term efficacy in enhancing post-stroke hand functional motor recovery and quantifiable indices of the participants response to a BCI-based intervention. To these aims, a longitudinal study will be performed in which subacute stroke participants will undergo a hand motor imagery (MI) training assisted by the Promotoer system, an EEG-based BCI system fully compliant with rehabilitation requirements.


This longitudinal 2-arm randomized controlled superiority trial will include 48 first ever, unilateral, subacute stroke participants, randomly assigned to 2 intervention groups: the BCI-assisted hand MI training and a hand MI training not supported by BCI. Both interventions are delivered (3 weekly session; 6 weeks) as add-on regimen to standard intensive rehabilitation. A multidimensional assessment will be performed at: randomization/pre-intervention, 48 h post-intervention, and at 1, 3 and 6 month/s after end of intervention. Primary outcome measure is the Fugl-Meyer Assessment (FMA, upper extremity) at 48 h post-intervention. Secondary outcome measures include: the upper extremity FMA at follow-up, the Modified Ashworth Scale, the Numeric Rating Scale for pain, the Action Research Arm Test, the National Institute of Health Stroke Scale, the Manual Muscle Test, all collected at the different timepoints as well as neurophysiological and neuroimaging measures.


We expect the BCI-based rewarding of hand MI practice to promote long-lasting retention of the early induced improvement in hand motor outcome and also, this clinical improvement to be sustained by a long-lasting neuroplasticity changes harnessed by the BCI-based intervention. Furthermore, the longitudinal multidimensional assessment will address the selection of those stroke participants who best benefit of a BCI-assisted therapy, consistently advancing the transfer of BCIs to a best clinical practice.

Trial registration

Name of registry: BCI-assisted MI Intervention in Subacute Stroke (Promotoer).

Trial registration number: NCT04353297; registration date on the platform: April, 15/2020.

Peer Review reports


Stroke is a major public health and social care concern worldwide [1]. The upper limb motor impairment commonly persists after stroke, and it represents the major contribution to long-term disability [2]. It has been estimated that the main clinical predictor of whether a patient would come back to work is the degree of upper extremity function [3]. Despite the intensive rehabilitation, the variability in the nature and extent of upper limb recovery remains a crucial factor affecting rehabilitation outcomes [4].

Electroencephalography (EEG)-based Brain-Computer Interface (BCI) is an emerging technology that enables a direct translation of brain activity into motor action [5]. Recently, EEG-based BCIs have been recognized as potential tools to promote functional motor recovery of upper limbs after stroke (for review see [6]). Several randomized controlled trials have shown that stroke patients can learn to modulate their EEG sensorimotor rhythms [7] to control external devices and this practice might facilitate neurological recovery both in subacute and chronic stroke phase [8,9,10].

We were previously successful in the design and validation of an EEG sensorimotor rhythms–based BCI combined with realistic visual feedback of upper limb to support hand motor imagery (MI) practice in stroke patients [1112]. Our previous pilot randomized controlled study [8] with the participation of 28 subacute stroke patients with severe motor deficit, suggested that 1 month BCI-assisted MI practice as an add-on intervention to the usual rehabilitation care was superior with respect to the add-on, 1 month MI training alone (ie., without BCI support) in improving hand functional motor outcomes (indicated by the significantly higher mean score at upper extremity Fugl-Meyer scale in the BCI with respect to control group). A greater involvement of the ipsilesional hemisphere, as reflected by a stronger motor-related EEG oscillatory activity and connectivity in response to MI of the paralyzed trained hand was also observed only in the BCI-assisted MI training condition. These promising findings corroborated the idea that a relatively low-cost technique (i.e. EEG-based BCI) can be exploited to deliver an efficacious rehabilitative intervention such as MI training and prompted us to undertake a translational effort by implementing an all-in-one BCI-supported MI training station– the Promotoer [13].

Yet, important questions remain to be addressed in order to improve the clinical viability of BCIs such as defining whether the expected early improvements in functional motor outcomes induced by the BCI-assisted MI training in subacute stroke [8] can be sustained in a long-term as it has been shown for other BCI-based approaches in chronic stroke patients [1014]. This requires advancements in the knowledge on brain functional re-organization early after stroke and on how this re-organization would correlate with the functional motor outcome (evidence-base medicine). Last but not least, the definition of the determinants of the patients response to treatment is paramount to optimize the process of personalized medicine in rehabilitation. We will address these questions by carrying out a randomized trial to eventually establish the fundamentals for a cost-effective use of EEG-based BCI technology to deliver a rehabilitative intervention such as the MI in hospitalized stroke patients.

Aim and hypotheses

The “Promotoer” study is a randomized controlled trial (RCT) designed to provide evidence for a significant early improvement of hand motor function induced by the BCI-assisted MI training operated via the Promotoer and for a persistency (up to 6 months) of such improvement. Task-specific training was reported to induce long-term improvements in arm motor function after stroke [15,16,17]. Thus, our hypothesis is that the BCI-based rewarding of hand MI tasks would promote long-lasting retention of early induced positive effect on motor performance with respect to MI tasks practiced in an open loop condition (ie, without BCI). Accordingly, the primary aim of the “Promotoer” RCT will be first to determine whether the BCI based intervention (MI-BCI) administered by means of a BCI system fully compatible with a clinical setting (the Promotoer), is superior to a non-BCI assisted MI training (MI Control) in improving hand motor function outcomes in sub-acute stroke patients admitted to the hospital for their standard rehabilitation care; secondly, we will test whether the efficacy of BCI-based intervention on hand motor function outcomes is sustained long-term after the end of intervention (6 months follow-up). A further hypothesis is that such clinical improvement would be sustained by a long-lasting neuroplasticity changes as harnessed by the BCI–based intervention. This hypothesis rises from current evidence for an early enhancement of post-stroke plastic changes enabled by BCI-based trainings [8,9,10]. To test this hypothesis, a longitudinal assessment of the brain network organization derived from advanced EEG signal processing (secondary objective) will be performed.

The heterogeneity of stroke makes prediction of treatment responders a great challenge [18]. The potential value of a combination of neurophysiological and neuroimaging biomarkers with the clinical assessment in predicting post-stroke motor recovery has been recently highlighted [19]. Our hypothesis is that the longitudinal combined functional, neurophysiological and neuroimaging assessment over 6 months from the intervention will allow for insights into biomarkers and potential predictors of patients response to the BCI-Promotoer training (secondary aim). To this purpose, well-recognized factors contributing to recovery after stroke such as the relation between clinical profile, lesion characteristics and patterns of post-stroke motor cortical re-organization (eg., ipsilesional/contralesional primary and non-primary motor areas, cortico-spinal tract integrity, severity of motor deficits at baseline; for review see [19]) will be taken into account.[…}


The Promotoer system. The Promoter is equipped with a computer, a commercial wireless EEG/EMG system (g.MOBIlab, g.tec medical engineering GmbH Austria), a screen for the therapist feedback (for the electroencephalographic – EEG activity and electromyographic- EMG activity monitoring) and screen for the ecological feedback to the participant; this ecological feedback is delivered by means of a custom software program that provides for (personalized) visual representation of the participant’s own hands. As such, this software allows the therapists to create an artificial reproduction of a given participant’s hand and forearm by adjusting a digitally created image in shape, size, skin color and orientation to match as much as possible the real hand and arm of the participant. Real-time feedback is provided by means of BCI2000 software [40]. The degree of EEG desynchronization over selected electrodes within selected frequencies (BCI control features) determines the vertical velocity of the cursor on the therapist’s screen and it operates the “virtual” hand software accordingly. The image is original as it is owned by the authors

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[Abstract] Can robotic gait rehabilitation plus Virtual Reality affect cognitive and behavioural outcomes in patients with chronic stroke? A randomized controlled trial involving three different protocols



The rehabilitation of cognitive and behavioral abnormalities in individuals with stroke is essential for promoting patient’s recovery and autonomy. The aim of our study is to evaluate the effects of robotic neurorehabilitation using Lokomat with and without VR on cognitive functioning and psychological well-being in stroke patients, as compared to traditional therapy.


Ninety stroke patients were included in this randomized controlled clinical trial. The patients were assigned to one of the three treatment groups, i.e. the Robotic Rehabilitation group undergoing robotic rehab with VR (RRG+VR), the Robotic Rehabilitation Group (RRG-VR) using robotics without VR, and the Conventional Rehabilitation group (CRG) submitted to conventional physiotherapy and cognitive treatment.


The analysis showed that either the robotic training (with and without VR) or the conventional rehabilitation led to significant improvements in the global cognitive functioning, mood, and executive functions, as well as in activities of daily living. However, only in the RRG+VR we observed a significant improvement in cognitive flexibility and shifting skills, selective attention/visual research, and quality of life, with regard to the perception of the mental and physical state.


Our study shows that robotic treatment, especially if associated with VR, may positively affect cognitive recovery and psychological well-being in patients with chronic stroke, thanks to the complex interation between movement and cognition.


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[Abstract] How brain imaging provides predictive biomarkers for therapeutic success in the context of virtual reality cognitive training


VR environments help improve rehabilitation of impaired complex cognitive functions

Combining neuroimaging and VR boosts ecological validity, generates practical gains

These are the first neurofunctional predictive biomarkers of VR cognitive training


As Virtual reality (VR) is increasingly used in neurological disorders such as stroke, traumatic brain injury, or attention deficit disorder, the question of how it impacts the brain’s neuronal activity and function becomes essential. VR can be combined with neuroimaging to offer invaluable insight into how the targeted brain areas respond to stimulation during neurorehabilitation training. That, in turn, could eventually serve as a predictive marker for therapeutic success. Functional magnetic resonance imaging (fMRI) identified neuronal activity related to blood flow to reveal with a high spatial resolution how activation patterns change, and restructuring occurs after VR training. Portable and quiet, electroencephalography (EEG) conveniently allows the clinician to track spontaneous electrical brain activity in high temporal resolution. Then, functional near-infrared spectroscopy (fNIRS) combines the spatial precision level of fMRIs with the portability and high temporal resolution of EEG to constitute an ideal measuring tool in virtual environments (VEs). This narrative review explores the role of VR and concurrent neuroimaging in cognitive rehabilitation.


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[ARTICLE] Key components of mechanical work predict outcomes in robotic stroke therapy – Full Text



Clinical practice typically emphasizes active involvement during therapy. However, traditional approaches can offer only general guidance on the form of involvement that would be most helpful to recovery. Beyond assisting movement, robots allow comprehensive methods for measuring practice behaviors, including the energetic input of the learner. Using data from our previous study of robot-assisted therapy, we examined how separate components of mechanical work contribute to predicting training outcomes.


Stroke survivors (n = 11) completed six sessions in two-weeks of upper extremity motor exploration (self-directed movement practice) training with customized forces, while a control group (n = 11) trained without assistance. We employed multiple regression analysis to predict patient outcomes with computed mechanical work as independent variables, including separate features for elbow versus shoulder joints, positive (concentric) and negative (eccentric), flexion and extension.


Our analysis showed that increases in total mechanical work during therapy were positively correlated with our final outcome metric, velocity range. Further analysis revealed that greater amounts of negative work at the shoulder and positive work at the elbow as the most important predictors of recovery (using cross-validated regression, R2 = 52%). However, the work features were likely mutually correlated, suggesting a prediction model that first removed shared variance (using PCA, R2 = 65–85%).


These results support robotic training for stroke survivors that increases energetic activity in eccentric shoulder and concentric elbow actions.


Assistance is often provided to aid limb movement during the rehabilitation process of stroke survivors. Many clinical researchers agree that active participation enhances recovery, and the goal of therapy should be to maximize “involvement” [12]. Too much assistance can actually discourage patient effort [3]. However, measurement of the degree to which patients are actually active is often difficult. Advances in rehabilitation devices allow for the measurement of forces and motion to better monitor patient activity. Here we investigate how upper limb mechanics during training relate to recovery.

Current tools for measuring physical activity during therapy offer limited information for describing interaction with the external environment or agent. While studies have shown that the intensity of therapy influences patient improvement, researchers have relied on simple metrics related to experimental conditions (e.g. movement repetitions, time-on-task, and therapy dosage) [45]. More sophisticated tools have been used to directly measure energetic contributions during therapy, such as oxygen consumption devices to measure metabolic cost [6] or electromyography to measure muscle activity [78]. However, such measures do not account for the time-varying force-motion relationships that occur during assisted movement. Robots easily measure both kinematic and kinetic variables facilitating the computation of energetic contributions in terms of mechanical power and work.

While energetic descriptions of movement have been widely studied, it has mainly focused on cyclic [9] or sustained movements, such as walking. Researchers have computed work and power to characterize normal and abnormal gait patterns [1011], to evaluate robot-assisted locomotion [12], and to reduce energetic costs when using exoskeletons [13]. Recently our work has focused on robotic augmentation of upper limb dynamics to facilitate vigorous movement during practice [1415]. We showed that stroke survivors increase total work output during force training [16]. Our intervention was fundamentally different than many previous strategies in that patients trained over a broader range of movements. In contrast to reaching studies [1718], such self-directed exploration allows for the examination of how energetics might depend on different force and motion states.

To better evaluate the variation in patient energetics, we believe more comprehensive measures are required beyond total expenditure of power or work. Researchers have also examined compartmentalized work and power measures in normal limb behaviors, for example, associating magnitudes of mechanical energy (e.g. positive/concentric and negative/eccentric work) with movement actions (e.g. flexion and extension) at individual joints [19]. Motor impairments due to stroke are also typically described in the context of motor actions of the limb. For example, stroke survivors exhibit abnormal flexion and extension synergies [20] and alterations in concentric and eccentric muscle contractions [2122]. As such, impairments can be associated with subcomponents of work and power. As patients interact differently in response to forces, subcomponents of work and power could reveal individual differences in involvement.

An emerging trend in rehabilitation is to identify certain factors that predict individual improvement in response to therapy. Researchers have identified patient biomarkers (impairment level, neurophysiological) correlated to patient outcomes providing better recommendations for therapy [23,24,25]. Similarly, our goal is to determine if particular types of work are more important to patient recovery. Such evaluation could inform decisions on design strategies and optimize assistance to each individual. In contrast to previous studies which have relied on independent analyses of many individual predictors, our analysis goal necessitates more rigorous statistical methods to deal with potentially related work features. One possible solution is to employ multiple regression analysis which can identify features most important for prediction.

In this paper, we investigate how the energetic contributions of stroke survivors during robot-assisted training relate to upper limb recovery. We employ well-established methods of inverse dynamics to estimate the torques generated by each patient during self-directed motor exploration training with customized forces. These methods conveniently allow us to quantify the energetic involvement of each individual joint in terms of mechanical work. We then use multiple regression analysis to identify which components of work are most important for predicting recovery. We hypothesize that positive work (concentric) in elbow extension is the best predictor of outcome. This study provides a key preliminary step towards evaluating energetic descriptions of patient involvement which can inform methods for upper limb robotic therapy practice.


Study participants

This investigation considered data collected from a previous study that featured 22 stroke survivors [15]. The main inclusion criteria included: 1) chronic stroke (8+ months post-stroke) 2) hemiparesis with moderate to severe arm impairment measured by the upper extremity portion of the Fugl-Meyer Assessment (UEFM score of 15–50) 3) primary cortex involvement. Each individual gave informed consent in accordance with the Northwestern University Institutional Review Board (IRB).


Experiment participants were asked to operate a two-degree of freedom robotic device with the affected arm (Fig. 1a). A custom video display system (not shown) provided visual feedback of the location of the wrist as the arm moved in the horizontal plane. During movement, the weight of the arm was supported. Movement data was collected at 200 Hz and filtered using a 5th order Butterworth low pass filter with a 12 Hz cutoff. Using anthropometric measurements recorded from each participant, we computed inverse kinematic relationships to obtain elbow and shoulder joint angles corresponding to endpoint position data. The robot control and instrumentation were mediated by a Simulink-based XPC Target computer, with a basic rate of 1 kHz. The robot controller compensated for the dynamics of the robot arm. A force sensor attached to the end-effector measured the human-robot interaction forces.

Experimental design. a Stroke survivors performed self-directed motor exploration by moving the robot handle in the horizontal plane. Measurements of their limb motion and the interaction forces were used to estimate the positive (concentric) and negative (eccentric) mechanical work exerted in different directions of shoulder and elbow joint motion. b The probability distribution of each individual’s movement velocities during unassisted motor exploration (top; blue indicates lower probability, red indicates higher probability, black contour line represents the 90th percentile velocity coverage) formed the basis for the design of customized training forces (bottom; red arrows indicate the direction and relative magnitude of forces applied, colored contour lines represents Gaussian model fit to velocity data)



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[ARTICLE] Review of the effects of soft robotic gloves for activity-based rehabilitation in individuals with reduced hand function and manual dexterity following a neurological event – Full Text

Despite limited scientific evidence, there is an increasing interest in soft robotic gloves to optimize hand- and finger-related functional abilities following a neurological event. This review maps evidence on the effects and effectiveness of soft robotic gloves for hand rehabilitation and, whenever possible, patients’ satisfaction. A systematized search of the literature was conducted using keywords structured around three areas: technology attributes, anatomy, and rehabilitation. A total of 272 titles, abstracts, and keywords were initially retrieved, and data were extracted out of 13 articles. Six articles investigated the effects of wearing a soft robotic glove and eight studied the effect or effectiveness of an intervention with it. Some statistically significant and meaningful beneficial effects were confirmed with the 29 outcome measures used. Finally, 11 articles also confirmed users’ satisfaction with regard to the soft robotic glove, while some articles also noticed an increased engagement in the rehabilitation program with this technology. Despite the heterogeneity across studies, soft robotic gloves stand out as a safe and promising technology to improve hand- and finger-related dexterity and functional performance. However, strengthened evidence of the effects or effectiveness of such devices is needed before their transition from laboratory to clinical practice. 

The hand and fingers are essential organs to perform a multitude of functional tasks in daily life, particularly to grasp and handle objects. In fact, the movements performed with the hand to grasp and handle objects, which can solicit up to 19 articulations driven by 29 muscles,1 can be grouped into two broad categories: power and precision grasps. Power grasping requires an individual performing gross motor tasks to generate large forces to firmly hold an object. In contrast, precision grasping requires an individual performing fine motor tasks to generate multiple levels of force to hold an object. The power grasps can be further characterized into cylindrical, spherical, or hook grasps whereas the precision grasps can be further categorized into pinch, tripodal, or lumbrical grasps (Figure 1).2 Whenever sensorimotor impairments of the hand and fingers develop as a result of a neurological event (e.g. stroke, spinal cord injury, Parkinson’s disease),3 the ability to grasp becomes jeopardized to various extents and may negatively impact functional abilities, as well as social participation and life satisfaction.4


Figure 1. Different types of power and precision grasps.

Despite intensive neurorehabilitation efforts, the likelihood of regaining optimal hand and finger-related functional abilities remains low following a neurological event. For examples, three months after a stroke, only 12% of survivors say they have no problem at all whereas 38% report major difficulties with hand and finger-related functional abilities,5,6 while 75% of individuals with a spinal cord injury at the cervical vertebral level (i.e. tetraplegia), who were asked which function they would most like to have restored, chose upper extremity function,7 with improvement in hand function being their highest-ranked goal.8 Therefore, it is no surprise that one of the most commonly expressed goals of individuals who have sustained a neurological event (i.e. stoke, tetraplegia) and rehabilitation professionals is to engage in neurorehabilitation interventions that can reduce hand and finger sensorimotor impairments, thus improving related functional abilities that are crucial for optimal social participation and life satisfaction.

Rehabilitation strategies designed to maximize hand and finger-related functional abilities are predominantly founded on activity-based therapy, integrating the principles of neuroplasticity.9 Such an approach requires these individuals to engage in meaningful hand- and finger-specific exercises that they must repeat intensively on a daily basis.10,11 In fact, to expect beneficial neuroplastic adaptations, animal studies focusing on gait suggest that up to 1000 to 2000 steps must be taken daily, whereas human studies focusing on grasping in stroke survivors suggest that at least 100 repetitions need to be completed daily.12 Although the evidence suggests the need, adhering to these principles13 remains challenging in clinical practice, especially given various time and productivity constraints. Indeed, it is common to observe in clinical practice that exercise programs are performed individually with direct supervision by a rehabilitation professional, which leads to productivity issues and limits the possibility of implementing interventions at high intensity.14,15 In fact, evidence suggests that the number of repetitions observed for upper extremity work in stroke survivors undergoing neurorehabilitation typically ranges between 12 and 60 repetitions per session, which is far below the number required to expect neuroplastic adaptations.16,17 In addition, recovery may be limited by lack of treatment time, due to the elevated demand for neurorehabilitation services and increased therapists’ workload, especially in publicly funded healthcare environments.18 As a result, individuals with sensorimotor deficits undergoing intensive functional rehabilitation may not achieve the full potential of their hand and fingers sensorimotor and related functional recovery and may reach a ‘recovery plateau’ earlier than expected during the rehabilitation process.

To overcome this challenge, the last decade has seen substantial progress in the development of soft robotic gloves that can facilitate hand and finger movements when performing activities of daily living (ADL) and instrumental activities (iADL) that require grasping objects.19 Moreover, these soft robotic gloves are predicted to be a promising adjunct neurorehabilitation intervention to potentiate the effects of conventional rehabilitation interventions and are now about to be introduced into clinical practice; their effects, however, remain uncertain due to a paucity of evidence. In this context, the present review aims to map, for the first time, the evidence of the effects of the soft robotic glove on the performance of hand- and finger-related functional activities (i.e. with vs. without the technology) and on hand and finger sensorimotor and related functional abilities (i.e. before vs. after an intervention using the technology), among individuals with hand and finger sensorimotor impairments and related disabilities and, whenever investigated, patients’ satisfaction related to the use of the soft robotic glove. Specifically, this review seeks to address the following objectives: (1) determine the effects of rehabilitation interventions using soft robotic gloves; and (2) determine the acceptability and the perceived usefulness of this technology.[…]

Continue —->  Review of the effects of soft robotic gloves for activity-based rehabilitation in individuals with reduced hand function and manual dexterity following a neurological event – Camille E Proulx, Myrka Beaulac, Mélissa David, Catryne Deguire, Catherine Haché, Florian Klug, Mario Kupnik, Johanne Higgins, Dany H. Gagnon, 2020

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[ARTICLE] Nervous System Pathophysiology: A critical time window for recovery extends beyond one-year post-stroke. – Full Text


The impact of rehabilitation on post-stroke motor recovery and its dependency on the patient’s chronicity remain unclear. The field has widely accepted the notion of a proportional recovery rule with a “critical window for recovery” within the first 3–6 mo poststroke. This hypothesis justifies the general cessation of physical therapy at chronic stages. However, the limits of this critical window have, so far, been poorly defined. In this analysis, we address this question, and we further explore the temporal structure of motor recovery using individual patient data from a homogeneous sample of 219 individuals with mild to moderate upper-limb hemiparesis. We observed that improvement in body function and structure was possible even at late chronic stages. A bootstrapping analysis revealed a gradient of enhanced sensitivity to treatment that extended beyond 12 mo poststroke. Clinical guidelines for rehabilitation should be revised in the context of this temporal structure.

NEW & NOTEWORTHY Previous studies in humans suggest that there is a 3- to 6-mo “critical window” of heightened neuroplasticity poststroke. We analyze the temporal structure of recovery in patients with hemiparesis and uncover a precise gradient of enhanced sensitivity to treatment that expands far beyond the limits of the so-called critical window. These findings highlight the need for providing therapy to patients at the chronic and late chronic stages.



The absolute incidence of stroke will continue to rise globally with a predicted 12 million stroke deaths in 2030 and 60 million stroke survivors worldwide (). Stroke leads to focal lesions in the brain due to cell death following hypoxia and inflammation, affecting both gray and white matter tracts (). After a stroke, a wide range of deficits can occur with varying onset latencies such as hemiparesis, abnormal posture, spatial hemineglect, aphasia, and spasticity, along with affective and cognitive deficits, chronic pain, and depression (). Due to improved treatment procedures during the acute stage of stroke (e.g., thrombolysis and thrombectomy), the associated reduction in stroke mortality has led to a greater proportion of patients facing impairments and needing long-term care and rehabilitation. However, prevention, diagnostics, rehabilitation, and prognostics of stroke recovery have not kept pace ().

Motor recovery after stroke has been widely operationalized as the individual’s change in two domains: 1) body function and structure (), whose improvement has been called “true recovery” () and refers to the restitution of a movement repertoire that the individual had before the injury; and 2) the ability to successfully perform the activities of daily living (). While the former is mainly due to the interaction of poststroke plasticity mechanisms and sensorimotor training, the latter is also influenced by the use of explicit and implicit compensatory strategies (). The most accepted measure for recovery of body function and structure is the change in the Fugl-Meyer Assessment of the upper extremity (UE-FM) scores (), while other clinical scales focus on the assessment of activities, such as the Chedoke Arm and Hand Activity Inventory (CAHAI) () or the Barthel Index for Activities of Daily Living (BI) ().

Poststroke motor recovery mostly follows a nonlinear trajectory that reaches asymptotic levels a few months after the injury (). This model suggests the existence of a period of heightened plasticity in which the patient seems to be more responsive to treatment, the so-called “critical window” for recovery. Aiming at characterizing the temporal structure of recovery, animal models and clinical research have identified a combination of mechanisms underlying neurological repair that seems to be unique to the injured brain, including neurogenesis, gliogenesis, axonal sprouting, and the rebalancing of excitation and inhibition in cortical networks (). This state of enhanced plasticity seems to be transient and interacts closely with sensorimotor training to facilitate the recovery of motor function (). However, there is no clear evidence of the exact temporal structure of enhanced responsiveness to treatment in humans, and as a result the optimal timing and intensity of treatment remain unclear. A systematic review of 14 studies suggested that, on average, recovery reaches a plateau at 15 wk poststroke for patients with severe hemiparesis and at 6.5 wk for patients with mild hemiparesis (). This study however failed to conduct a meta-analysis due to substantial heterogeneity of the sample and protocols. Currently, an ongoing clinical trial is investigating the existence and the duration of a critical window of enhanced neuroplasticity in humans following ischemic stroke (). Based on the assumption of the existence of this critical period, the SMARTS 2 trial (NCT02292251) () is currently investigating the effect of early and intensive therapy on upper extremity motor recovery. Sharing the same research question, the Critical Periods After Stroke Study (CPASS) is a large ongoing randomized controlled trial that focuses on determining the optimal time after stroke for intensive motor training (). To contribute to the delineation of a temporal structure of stroke recovery in humans, we performed an analysis of individual patient clinical data from 219 subjects with upper-limb hemiparesis, who followed occupational therapy (OT) or a virtual reality (VR)-based training protocol using the Rehabilitation Gaming System (RGS) () (Fig. S1 in Supplemental Material; all Supplemental material is available at We show that physical therapy has a significant impact on the function of the upper extremity (UE) at all periods poststroke considered, uncovering a gradient of responsiveness to treatment that extends >12 mo poststroke.[…]

Continue —->  Nervous System Pathophysiology: A critical time window for recovery extends beyond one-year post-stroke

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[ARTICLE] Literature Review on the Effects of tDCS Coupled with Robotic Therapy in Post Stroke Upper Limb Rehabilitation – Full Text

Today neurological diseases such as stroke represent one of the leading cause of long-term disability. Many research efforts have been focused on designing new and effective rehabilitation strategies. In particular, robotic treatment for upper limb stroke rehabilitation has received significant attention due to its ability to provide high-intensity and repetitive movement therapy with less effort than traditional methods. In addition, the development of non-invasive brain stimulation techniques such as transcranial Direct Current Stimulation (tDCS) has also demonstrated the capability of modulating brain excitability thus increasing motor performance. The combination of these two methods is expected to enhance functional and motor recovery after stroke; to this purpose, the current trends in this research field are presented and discussed through an in-depth analysis of the state-of-the-art. The heterogeneity and the restricted number of collected studies make difficult to perform a systematic review. However, the literature analysis of the published data seems to demonstrate that the association of tDCS with robotic training has the same clinical gain derived from robotic therapy alone. Future studies should investigate combined approach tailored to the individual patient’s characteristics, critically evaluating the brain areas to be targeted and the induced functional changes.


Stroke is one of the leading factors of morbidity and mortality worldwide (Warlow et al., 2001).

In Italy, stroke annual incidence varies between 175/100.000 and 360/100.000 in men and between 130/100.000 and 273/100.000 in women (Sacco et al., 2011). Further, still in Italy, a total of 196.000 individuals are affected by stroke each year, 80% are new episodes and 20% are relapses (Gensini, 2005).

Activities of daily living (ADLs) and human quality of life strongly depend on upper limb functioning (Franceschini et al., 2010). Therefore, one of the goals of post-stroke upper limb rehabilitation is to recover arm and hand functions, and enable the patients to perform ADLs independently.

It is shown in the literature that intensive as well as task-specific training can be very effective in upper limb rehabilitation treatments after stroke (Feys et al., 2004Lo et al., 2010Klamroth-Marganska et al., 2014); this training should be repetitive, challenging and functional for the patients. To this purpose, robotics represents a key enabling technology for addressing these requirements for a well-stratified group of stroke patients (i.e., moderate-to-severe subjects). Clinical studies, varying in design and methods, have examined the effect of robotic devices on upper-limb and lower-limb rehabilitation in a clinical setting (Prange et al., 2006Brewer et al., 2007Mehrholz et al., 2015). Moreover, in a multicenter randomized controlled trial on moderate-to-severe chronic stroke patients, robotic therapy resulted superior to usual care and not inferior to intensive conventional rehabilitation treatment in terms of recovery of upper limb motor function (Lo et al., 2010). In addition, using robotic devices allows delivering new therapy constraints to maximize the required movement pattern (Kwakkel et al., 2007). Therefore, it is possible to control task learning phase more easily with robots than with traditional therapeutic techniques, since robots allows patients to perform guided movements on predefined pathways and avoid possible uncontrolled movements (Kwakkel et al., 2007).

Despite the interesting advancements in this area, the type of therapy leading to optimal results remains controversial and elusive and patients are often left with considerable disability (Bastani and Jaberzadeh, 2012).

Recently, the application of non-invasive neuro-modulation strategies to counteract inter-hemispheric imbalance has been acquiring a growing interest in post-stroke rehabilitation (Duque et al., 2005Hummel and Cohen, 2006Bolognini et al., 2009Kandel et al., 2012). The adjunct of non-invasive interventions, such as the electrical brain stimulation or magnetic brain stimulation (Di Lazzaro et al., 2016), might be used to speed-up and maximize the potential benefit of rehabilitation treatments. In particular, transcranial Direct Current Stimulation (tDCS) may play an important role in stroke recovery since its capability to modify cortical excitability and neural activity (Lefaucheur, 2016Lefaucheur et al., 2017).

In fact, modulating the excitability of a targeted brain region non-invasively, can favor a normal balance in the interhemispheric interaction and, hence, facilitate the recovery of motor functions of the paretic limb (Kandel et al., 2012).

tDCS consists of applying low-intensity current (1–2 mA) between two or multiple small electrodes on the scalp (Dmochowski et al., 2011). Depending on the electrode polarity, an opposite polarization of brain tissues can be induced with consequent modification of the resting membrane potential. Anodal stimulation will induce depolarization and increased cortical excitability; cathodal stimulation will induce hyperpolarization and decreased cortical excitability (Nitsche and Paulus, 2000Fregni et al., 2005).

In the past, several studies have demonstrated a tDCS effect in terms of increased primary motor cortex activation assessed with fMRI (Hummel et al., 2005Lindenberg et al., 2010).

The inter-hemispheric inhibitory competition model (Duque et al., 2005) implies that, to restore the interhemispheric balance altered after a stroke, one can either increase the excitability of the affected hemisphere with the anodal tDCS, or decrease the activity of the healthy hemisphere with cathodal tDCS (Hummel and Cohen, 2006).

The use of bilateral tDCS (applying simultaneously anodal electrode on the affected hemisphere and cathodal electrode on the unaffected hemisphere, Tazoe et al., 2014) could also be an effective strategy to produce interhemispheric rebalancing effects. Notwithstanding the promising achievements, the debate on tDCS efficacy in neurorehabilitation is still active and not entirely examined (Stagg and Johansen-Berg, 2013).

The application of tDCS might also have an impact on shoulder abduction (SABD) loading effects in individuals with moderate to severe chronic stroke; however, it is insufficient to make significant changes at higher SABD loads (Yao et al., 2015).

Furthermore, several neuromodulatory protocols have been applied together with robotic gait training to induce cortical plasticity and promote motor recovery after stroke. Motor excitability induced by paired associative stimulation, i.e., repetitive transcranial magnetic stimulation (rTMS) and tDCS has shown to be a potential neuromodulatory adjuvant of walking rehabilitation in patients with chronic stroke (Jayaram and Stinear, 2009) although there was no evidence regarding the efficacy of these protocols with respect to the others.

On the other hand, robot-assisted repetition with electromechanical gait trainer (Hesse et al., 1997Hesse and Uhlenbrock, 2000) improved gait performance and maintained functional recovery at follow-up even during the chronic phase of stroke (Peurala et al., 2005Dias et al., 2007). This could be likely due to the gait-like movement that allowed patients to practice a complete gait cycle, achieving better symmetric and physiological walking (Dias et al., 2007).

In this context, the adjunct of tDCS (delivered over the lower extremity motor cortex) to robotic locomotor exercises showed the capability to enhance the effectiveness of robotic gait training in chronic stroke patients (Danzl et al., 2013).

Conversely, while administering tDCS did not produce any reverse effects on chronic stroke patients, on the other hand it seemed to have no additional effect on robot-assisted gait training (Geroin et al., 2011). This could be due to the peculiar neural organization of locomotion, which involves both cortical (motor cortex) and spinal (central pattern generators) control (Dietz, 2002Geroin et al., 2011).

Recently, another study has supported the hypothesis that anodal tDCS combined with cathodal transcutaneous spinal direct current stimulation (tsDCS) may be useful to improve the effects of robotic gait training in chronic stroke (Picelli et al., 2015).

Finally, combination of tDCS and robotic training has shown a promising strategy for improving arm, hand and lower extremity motor functions in persons with incomplete spinal cord injury (Raithatha et al., 2016Yozbatiran et al., 2016).

All these approaches justify the growing interest of the scientific community in the evaluation of the effects of upper limb robot-aided motor training coupled with tDCS in stroke, relying on the adjunct of tDCS to further enhance primary effects of motor recovery (Triccas et al., 2016).

This paper intends to carry out an in-depth study of the literature regarding the effects of the combined use of tDCS and RT on motor and functional recovery in post stroke subjects. Moreover, the expected added value provided by this work is to complete the current knowledge in the neurorehabilitation field, by critically evaluating and comparing (when possible) the available results as well as discussing inconsistencies and possible issues. As a final goal, indications for the development of future and more specific rehabilitation protocols tailored to subject’s needs are provided.

The paper is structured as follows. In Section “Overview of the Main Studies on tDCS Coupled with Upper-Limb Robotic Treatment” an overview of clinical studies that analyze effects of tDCS combined with upper limb robotic therapy (RT) is reported.

Section “Discussion” presents a critical discussion of the presented studies aimed to assess the efficacy of this novel combined approach. Finally, Section “Conclusions and future perspectives” reports final considerations and future suggestions.

Overview of the Main Studies on tDCS Coupled with Upper-Limb Robotic Treatment

The study of the effects deriving from the coupled use of tDCS and RT represents a relatively young field of interest. In fact, the number of studies that have tried to investigate and prove the successful combination of these two techniques is limited.

A wide literature search updated to January 2017 has been conducted resorting to the main databases, such as Pubmed Central (PMC), Cochrane, Scopus, Google Scholar. The following keywords have been employed: tDCS AND stroke* OR ictus OR hemiplegia* AND robot* OR robotic therapy*, upper-limb rehabilitation, brain stimulation techniques, neurorehabilitation, rehabilitation robotics. Studies have been included only when focused on the novel therapeutic approach based on tDCS combined with robotic upper limb therapy.

The following inclusion criteria have been utilized:

1. Be a single session clinical trial (i.e., compare pre-treatment and post-treatment performance) or controlled trial (i.e., clinical trial with a control group, either randomized or not).

2. Involve stroke patients.

3. Concern movement therapy with a robotic device.

4. Include transcranial Direct Current Stimulation (tDCS) as Non-Invasive Brain Stimulation Technique.

5. Focus on upper-limb motor control (and possibly functional abilities).

6. Use relevant motor control and functional ability outcome measures.

7. Be a full-length publication in a peer-reviewed journal.

To enable the most complete overview of the current literature, the search has not been limited by patient subgroups (i.e., acute, subacute, or chronic) or by language.

A flowchart of the search and inclusion process is shown in Figure 1. A total of 830 papers has been gathered by using the aforementioned search method. The abstracts matching the inclusion criteria have been selected. When appropriate, the full paper has been read. Therefore, from the initial 830 papers, 820 have been excluded since they did not meet the inclusion criteria. The remaining 10 papers have been carefully read. Eight studies are journal papers while 2 are conference papers.

Figure 1. Flowchart of the search and inclusion process.



Continue —->  Frontiers | Literature Review on the Effects of tDCS Coupled with Robotic Therapy in Post Stroke Upper Limb Rehabilitation | Human Neuroscience

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[Abstract] Robot-assisted therapy for arm recovery for stroke patients: state of the art and clinical implication


Introduction: Robot-assisted therapy is an emerging approach that performs highly repetitive, intensive, task oriented and quantifiable neuro-rehabilitation. In the last decades, it has been increasingly used in a wide range of neurological central nervous system conditions implying an upper limb paresis. Results from the studies are controversial, for the many types of robots and their features often not accompanied by specific clinical indications about the target functions, fundamental for the individualized neurorehabilitation program.

Areas covered: This article reviews the state of the art and perspectives of robotics in post-stroke rehabilitation for upper limb recovery. Classifications and features of robots have been reported in accordance with technological and clinical contents, together with the definition of determinants specific for each patient, that could modify the efficacy of robotic treatments. The possibility of combining robotic intervention with other therapies has also been discussed.

Expert commentary: The recent wide diffusion of robots in neurorehabilitation has generated a confusion due to the commingling of technical and clinical aspects not previously clarified. Our critical review provides a possible hypothesis about how to match a robot with subject’s upper limb functional abilities, but also highlights the need of organizing a clinical consensus conference about the robotic therapy.

Article Highlights

Robotic neurorehabilitation has the potential to improve the quality and intensity of rehabilitation treatments in order to promote motor-cognitive recovery following a central nervous system disease.

Controversial results in literature maybe generated by confusion in the use of robots related to many technological and clinical features, and emphasized by excessive optimism or scepticism about this technology.

Budgets spent for robots in rehabilitation are expected to grow dramatically in the next future, but there is the need of evidence-based proofs to balance the business push.

There is need of further researches in motor-cognitive technological rehabilitation in order to better understand the gain that robotic therapy could add to conventional therapy in relation to the patient’s cognitive reserve.

There is a need for clinical consensus conferences that might give clinical indication to end users.
via Robot-assisted therapy for arm recovery for stroke patients: state of the art and clinical implication: Expert Review of Medical Devices: Vol 0, No 0

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[ARTICLE] Cost Analysis of a Home-Based Virtual Reality Rehabilitation to Improve Upper Limb Function in Stroke Survivors – Full Text PDF


Loss of arm function occurs in up to 85% of stroke survivors. Home-based telerehabilitation is a viable approach for upper limb training post-stroke when rehabilitation services are not available. Method: A costing analysis of a telerehabilitation program was conducted under several scenarios, alongside a single-blind two-arm randomized controlled trial with participants randomly allocated to control (N=25) or intervention group (N=26). Detailed analysis of the cost for two different scenarios for providing telerehabilitation were conducted. The fixed costs of the telerehabilitation are an important determinant of the total costs of the program. The detailed breakdown of the costs allows for costs of future proposed telerehabilitation programs to be easily estimated. The costs analysis found that a program supplying all required technology costs between CAD$475 per patient and CAD$482 per patient, while a program supplying only a camera would have total costs between CAD$242 per patient and $245 per patient. The findings of this study support the potential implementation of telerehabilitation for stroke survivors for improving accessibility to rehabilitation services. This cost-analysis study will facilitate the implementation and future research on cost-effectiveness of such interventions.

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via Cost Analysis of a Home-Based Virtual Reality Rehabilitation to Improve Upper Limb Function in Stroke Survivors | Veras | Global Journal of Health Science | CCSE

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[Abstract] Pushing the limits of recovery in chronic stroke survivors: User perceptions of the Queen Square Upper Limb Neurorehabilitation Programme – Full Text PDF


Introduction: The Queen Square Upper Limb (QSUL) Neurorehabilitation Programme is a clinical service within the National Health Service in the United Kingdom that provides 90 hours of therapy over three weeks to stroke survivors with persistent upper limb impairment. This study aimed to explore the perceptions of participants of this programme, including clinicians, stroke survivors and carers.

Design: Descriptive qualitative.

Setting: Clinical outpatient neurorehabilitation service.

Participants: Clinicians (physiotherapists, occupational therapists, rehabilitation assistants) involved in the delivery of the QSUL Programme, as well as stroke survivors and carers who had participated in the programme were purposively sampled. Each focus group followed a series of semi-structured, open questions that were tailored to the clinical or stroke group. One independent researcher facilitated all focus groups, which were audio-recorded, transcribed verbatim and analysed by four researchers using a thematic approach to identify main themes.

Results: Four focus groups were completed: three including stroke survivors (n = 16) and carers (n = 2), and one including clinicians (n = 11). The main stroke survivor themes related to psychosocial aspects of the programme (″ you feel valued as an individual ″), as well as the behavioural training provided (″ gruelling, yet rewarding& [Prime]). The main clinician themes also included psychosocial aspects of the programme (″ patient driven ethos − no barriers, no rules ″), and knowledge, skills and resources of clinicians (″ it is more than intensity, it is complex ″).

Conclusions: As an intervention, the QSUL Programme is both comprehensive and complex. The impact of participation in the programme spans psychosocial and behavioural domains from the perspectives of both the stroke survivor and clinician.

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via Pushing the limits of recovery in chronic stroke survivors: User perceptions of the Queen Square Upper Limb Neurorehabilitation Programme. | medRxiv

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