Posts Tagged paresis

[Abstract] How to perform mirror therapy after stroke? Evidence from a meta-analysis

Abstract

BACKGROUND:

A recently updated Cochrane review for mirror therapy (MT) showed a high level of evidence in the treatment of hemiparesis after stroke. However, the therapeutic protocols used in the individual studies showed significant variability.

OBJECTIVE:

A secondary meta-analysis was performed to detect which parameters of these protocols may influence the effect of MT for upper limb paresis after stroke.

METHODS:

Trials included in the Cochrane review, which published data for motor function / impairment of the upper limb, were subjected to this analysis. Trials or trial arms that used MT as group therapy or combined it with electrical or magnetic stimulation were excluded. The analysis focused on the parameters mirror size, uni- or bilateral movement execution, and type of exercise. Data were pooled by calculating the total weighted standardized mean difference and the 95% confidence interval.

RESULTS:

Overall, 32 trials were included. The use of a large mirror compared to a small mirror showed a higher effect on motor function. Movements executed unilaterally showed a higher effect on motor function than a bilateral execution. MT exercises including manipulation of objects showed a minor effect on motor function compared to movements excluding the manipulation of objects. None of the subgroup differences reached statistical significance.

CONCLUSIONS:

The results of this analysis suggest that the effects on both motor function and impairment of the affected upper limb depend on the therapy protocol. They furthermore indicate that a large mirror, unilateral movement execution and exercises without objects may be parameters that enhance the effects of MT for improving motor function after stroke.

 

via How to perform mirror therapy after stroke? Evidence from a meta-analysis. – PubMed – NCBI

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[ARTICLE] Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling – Full Text

Abstract

Background

Research efforts in neurorehabilitation technologies have been directed towards creating robotic exoskeletons to restore motor function in impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had only modest clinical impact. A major limitation is the inability to enable exoskeleton voluntary control in neurologically impaired individuals. This hinders the possibility of optimally inducing the activity-driven neuroplastic changes that are required for recovery.

Methods

We have developed a patient-specific computational model of the human musculoskeletal system controlled via neural surrogates, i.e., electromyography-derived neural activations to muscles. The electromyography-driven musculoskeletal model was synthesized into a human-machine interface (HMI) that enabled poststroke and incomplete spinal cord injury patients to voluntarily control multiple joints in a multifunctional robotic exoskeleton in real time.

Results

We demonstrated patients’ control accuracy across a wide range of lower-extremity motor tasks. Remarkably, an increased level of exoskeleton assistance always resulted in a reduction in both amplitude and variability in muscle activations as well as in the mechanical moments required to perform a motor task. Since small discrepancies in onset time between human limb movement and that of the parallel exoskeleton would potentially increase human neuromuscular effort, these results demonstrate that the developed HMI precisely synchronizes the device actuation with residual voluntary muscle contraction capacity in neurologically impaired patients.

Conclusions

Continuous voluntary control of robotic exoskeletons (i.e. event-free and task-independent) has never been demonstrated before in populations with paretic and spastic-like muscle activity, such as those investigated in this study. Our proposed methodology may open new avenues for harnessing residual neuromuscular function in neurologically impaired individuals via symbiotic wearable robots.

Background

The ability to walk directly relates to quality of life. Neurological lesions such as those underlying stroke and spinal cord injury (SCI) often result in severe motor impairments (i.e., paresis, spasticity, abnormal joint couplings) that compromise an individual’s motor capacity and health throughout the life span. For several decades, scientific effort in rehabilitation robotics has been directed towards exoskeletons that can help enhance motor capacity in neurologically impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had limited performance when tested in healthy individuals [1] and have achieved only modest clinical impact in neurologically impaired patients [2], e.g., stroke [34], SCI patients [5]. […]

 

Continue —>  Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling | Journal of NeuroEngineering and Rehabilitation | Full Text

Fig. 1

Fig. 1 Enter aSchematic representation of the real-time modeling framework and its communication with the robotic exoskeleton. The whole framework is operated by a Raspberry Pi 3 single-board computer. The framework consists of five main components: a The EMG plugin collects muscle bioelectric signals from wearable active electrodes and transfers them to the EMG-driven model. b The B-spline component computes musculotendon length (Lmt) and moment arm (MA) values from joint angles collected via robotic exoskeleton sensors. c The EMG-driven model uses input EMG, Lmt and MA data to compute the resulting mechanical forces in 12 lower-extremity musculotendon units (Table 1) and joint moment about the degrees of freedom of knee flexion-extension and ankle plantar-dorsiflexion. d The offline calibration procedure identifies internal parameters of the model that vary non-linearly across individuals. These include optimal fiber length and tendon slack length, muscle maximal isometric force, and excitation-to-activation shape factors. eThe exoskeleton plugin converts EMG-driven model-based joint moment estimates into exoskeleton control commands. Please refer to the Methods section for an in-depth description caption

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[Abstract + References] Multimodal Head-Mounted Virtual-Reality Brain-Computer Interface for Stroke Rehabilitation – Conference paper

Abstract

Rehabilitation after stroke requires the exploitation of active movement by the patient in order to efficiently re-train the affected side. Individuals with severe stroke cannot benefit from many training solutions since they have paresis and/or spasticity, limiting volitional movement. Nonetheless, research has shown that individuals with severe stroke may have modest benefits from action observation, virtual reality, and neurofeedback from brain-computer interfaces (BCIs). In this study, we combined the principles of action observation in VR together with BCI neurofeedback for stroke rehabilitation to try to elicit optimal rehabilitation gains. Here, we illustrate the development of the REINVENT platform, which takes post-stroke brain signals indicating an attempt to move and drives a virtual avatar arm, providing patient-driven action observation in head-mounted VR. We also present a longitudinal case study with a single individual to demonstrate the feasibility and potentially efficacy of the REINVENT system.

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via Multimodal Head-Mounted Virtual-Reality Brain-Computer Interface for Stroke Rehabilitation | SpringerLink

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[REVIEW ARTICLE] Robot-Assisted Therapy in Upper Extremity Hemiparesis: Overview of an Evidence-Based Approach – Full Text

Robot-mediated therapy is an innovative form of rehabilitation that enables highly repetitive, intensive, adaptive, and quantifiable physical training. It has been increasingly used to restore loss of motor function, mainly in stroke survivors suffering from an upper limb paresis. Multiple studies collated in a growing number of review articles showed the positive effects on motor impairment, less clearly on functional limitations. After describing the current status of robotic therapy after upper limb paresis due to stroke, this overview addresses basic principles related to robotic therapy applied to upper limb paresis. We demonstrate how this innovation is an evidence-based approach in that it meets both the improved clinical and more fundamental knowledge-base about regaining effective motor function after stroke and the need of more objective, flexible and controlled therapeutic paradigms.

Introduction

Robot-mediated rehabilitation is an innovative exercise-based therapy using robotic devices that enable the implementation of highly repetitive, intensive, adaptive, and quantifiable physical training. Since the first clinical studies with the MIT-Manus robot (1), robotic applications have been increasingly used to restore loss of motor function, mainly in stroke survivors suffering from an upper limb paresis but also in cerebral palsy (2), multiple sclerosis (3), spinal cord injury (4), and other disease types. Thus, multiple studies suggested that robot-assisted training, integrated into a multidisciplinary program, resulted in an additional reduction of motor impairments in comparison to usual care alone in different stages of stroke recovery: namely, acute (57), subacute (18), and chronic phases after the stroke onset (911). Typically, patients engaged in the robotic therapy showed an impairment reduction of 5 points or more in the Fugl-Meyer assessment as compared to usual care. Of notice, rehabilitation studies conducted during the chronic stroke phase suggest that a 5-point differential represents the minimum clinically important difference (MCID), i.e., the magnitude of change that is necessary to produce real-world benefits for patients (12). These results were collated in multiple review articles and meta-analyses (1317). In contrast, the advantage of robotic training over usual care in terms of functional benefit is less clear, but there are recent results that suggest how best to organize training to achieve superior results in terms of both impairment and function (18). Indeed, the use of the robotic tool has allowed us the parse and study the ingredients that should form an efficacious and efficient rehabilitation program. The aim of this paper is to provide a general overview of the current state of robotic training in upper limb rehabilitation after stroke, to analyze the rationale behind its use, and to discuss our working model on how to more effectively employ robotics to promote motor recovery after stroke.

Upper Extremity Robotic Therapy: Current Status

Robotic systems used in the field of neurorehabilitation can be organized under two basic categories: exoskeleton and end-effector type robots. Exoskeleton robotic systems allow us to accurately determine the kinematic configuration of human joints, while end-effector type robots exert forces only in the most distal part of the affected limb. A growing number of commercial robotic devices have been developed employing either configuration. Examples of exoskeleton type include the Armeo®Spring, Armeo®Power, and Myomo® and of end-effector type include the InMotion™, Burt®, Kinarm™ and REAplan®. Both categories enable the implementation of intensive training and there are many other devices in different stages of development or commercialization (1920).

The last decade has seen an exponential growth in both the number of devices as well as clinical trials. The results coalesced in a set of systematic reviews, meta-analyses (1317) and guidelines such as those published by the American Heart Association and the Veterans Administration (AHA and VA) (21). There is a clear consensus that upper limb therapy using robotic devices over 30–60-min sessions, is safe despite the larger number of movement repetitions (14).

This technic is feasible and showed a high rate of eligibility; in the VA ROBOTICS (911) study, nearly two thirds of interviewed stroke survivors were enrolled in the study. As a comparison the EXCITE cohort of constraint-induced movement therapy enrolled only 6% of the screened patients participated (22). On that issue, it is relevant to notice the admission criteria of both chronic stroke studies. ROBOTICS enrolled subjects with Fugl-Meyer assessment (FMA) of 38 or lower (out of 66) while EXCITE typically enrolled subjects with an FMA of 42 or higher. Duret and colleagues demonstrated that the target population, based on motor impairments, seems to be broader in the robotic intervention which includes patients with severe motor impairments, a group that typically has not seen much benefit from usual care (23). Indeed, Duret found that more severely impaired patients benefited more from robot-assisted training and that co-factors such as age, aphasia, and neglect had no impact on the amount of repetitive movements performed and were not contraindicated. Furthermore, all patients enrolled in robotic training were satisfied with the intervention. This result is consistent with the literature (24).

The main outcome result is that robotic therapy led to significantly more improvement in impairment as compared to conventional usual care, but only slightly more on motor function of the limb segments targeted by the robotic device (16). For example, Bertani et al. (15) and Zhang et al. (17) found that robotic training was more effective in reducing motor impairment than conventional usual care therapy in patients with chronic stroke, and further meta-analyses suggested that using robotic therapy as an adjunct to conventional usual care treatment is more effective than robotic training alone (1317). Other examples of disproven beliefs: many rehabilitation professionals mistakenly expected significant increase of muscle hyperactivity and shoulder pain due to the intensive training. Most studies showed just the opposite, i.e., that intensive robotic training was associated with tone reduction as compared to the usual care groups (92526). These results are shattering the resistance to the widespread adoption of robotic therapy as a therapeutic modality post-stroke.

That said, not all is rosy. Superior changes in functional outcomes were more controversial until the very last years as most studies and reviews concluded that robotic therapy did not improve activities of daily living beyond traditional care. One first step was reached in 2015 with Mehrholz et al. (14), who found that robotic therapy can provide more functional benefits when compared to other interventions however with a quality of evidence low to very low. 2018 may have seen a decisive step in favor of robotic as the latest meta-analysis conducted by Mehrholz et al. (27) concluded that robot-assisted arm training may improve activities of daily living in the acute phase after stroke with a high quality of evidence However, the results must be interpreted with caution because of the high variability in trial designs as evidenced by the multicenter study (28) in which robotic rehabilitation using the Armeo®Spring, a non-motorized device, was compared to self-management with negative results on motor impairments and potential functional benefits in the robotic group.

The Robot Assisted Training for the Upper Limb after Stroke (RATULS) study (29) might clarify things and put everyone in agreement on the topic. Of notice, RATULS goes beyond the Veterans Administration ROBOTICS with chronic stroke or the French REM_AVC study with subacute stroke. RATULS included 770 stroke patients and covered all stroke phases, from acute to chronic, and it included a positive meaningful control in addition to usual care.[…]

 

Continue —->  Frontiers | Robot-Assisted Therapy in Upper Extremity Hemiparesis: Overview of an Evidence-Based Approach | Neurology

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[Abstract] Immersive virtual reality mirror therapy for upper limb recovery following stroke – A pilot study

Abstract

Objective This study was designed to examine the feasibility of immersive virtual reality(VR) mirror therapy for upper limb paresis after stroke using a head-mounted display, and provide preliminary evidence of efficacy.

Design Ten outpatients with chronic stroke, upper limb hemiparesis, and a low predisposition for motion sickness completed a 12-session program of 30 minutes each of immersive VR mirror therapy. The VR system provided the illusion of movement in the hemiparetic upper limb while suppressing the visual representation of the non-paretic side. Feasibility was assessed via patient compliance, adverse event tracking, the System Usability Scale, and the Simulator Sickness Questionnaire. Preliminary efficacy was evaluated using the Fugl-Meyer Upper Extremity (FM-UE) and Action Research Arm Test.

Results Immersive VR mirror therapy for patients with chronic stroke was safe, well-tolerated, and without adverse events, such as simulator sickness. Motor outcomes revealed a small improvement for the FM-UE from 21.7 (SD= 8.68) to 22.8 (SD= 9.19) that did not achieve statistical significance (p=0.084).

Conclusion Four weeks of immersive virtual reality mirror therapy was well-tolerated by chronic stroke patients. Our findings support further clinical trials of immersive VR technologies and visually-enhanced mirror therapies for stroke survivors.

via Immersive virtual reality mirror therapy for upper limb reco… : American Journal of Physical Medicine & Rehabilitation

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[Abstract] Brain-Machine Interface in Chronic Stroke: Randomized Trial Long-Term Follow-up

Background. Brain-machine interfaces (BMIs) have been recently proposed as a new tool to induce functional recovery in stroke patients.

Objective. Here we evaluated long-term effects of BMI training and physiotherapy in motor function of severely paralyzed chronic stroke patients 6 months after intervention.

Methods. A total of 30 chronic stroke patients with severe hand paresis from our previous study were invited, and 28 underwent follow-up assessments. BMI training included voluntary desynchronization of ipsilesional EEG-sensorimotor rhythms triggering paretic upper-limb movements via robotic orthoses (experimental group, n = 16) or random orthoses movements (sham group, n = 12). Both groups received identical physiotherapy following BMI sessions and a home-based training program after intervention. Upper-limb motor assessment scores, electromyography (EMG), and functional magnetic resonance imaging (fMRI) were assessed before (Pre), immediately after (Post1), and 6 months after intervention (Post2).

Results. The experimental group presented with upper-limb Fugl-Meyer assessment (cFMA) scores significantly higher in Post2 (13.44 ± 1.96) as compared with the Pre session (11.16 ± 1.73; P = .015) and no significant changes between Post1 and Post2 sessions. The Sham group showed no significant changes on cFMA scores. Ashworth scores and EMG activity in both groups increased from Post1 to Post2. Moreover, fMRI-BOLD laterality index showed no significant difference from Pre or Post1 to Post2 sessions.

Conclusions. BMI-based rehabilitation promotes long-lasting improvements in motor function of chronic stroke patients with severe paresis and represents a promising strategy in severe stroke neurorehabilitation.

via Brain-Machine Interface in Chronic Stroke: Randomized Trial Long-Term Follow-up – Ander Ramos-Murguialday, Marco R. Curado, Doris Broetz, Özge Yilmaz, Fabricio L. Brasil, Giulia Liberati, Eliana Garcia-Cossio, Woosang Cho, Andrea Caria, Leonardo G. Cohen, Niels Birbaumer, 2019

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[Abstract] Brain-Machine Interface in Chronic Stroke: Randomized Trial Long-Term Follow-up

Background. Brain-machine interfaces (BMIs) have been recently proposed as a new tool to induce functional recovery in stroke patients.

Objective. Here we evaluated long-term effects of BMI training and physiotherapy in motor function of severely paralyzed chronic stroke patients 6 months after intervention.

Methods. A total of 30 chronic stroke patients with severe hand paresis from our previous study were invited, and 28 underwent follow-up assessments. BMI training included voluntary desynchronization of ipsilesional EEG-sensorimotor rhythms triggering paretic upper-limb movements via robotic orthoses (experimental group, n = 16) or random orthoses movements (sham group, n = 12). Both groups received identical physiotherapy following BMI sessions and a home-based training program after intervention. Upper-limb motor assessment scores, electromyography (EMG), and functional magnetic resonance imaging (fMRI) were assessed before (Pre), immediately after (Post1), and 6 months after intervention (Post2).

Results. The experimental group presented with upper-limb Fugl-Meyer assessment (cFMA) scores significantly higher in Post2 (13.44 ± 1.96) as compared with the Pre session (11.16 ± 1.73; P = .015) and no significant changes between Post1 and Post2 sessions. The Sham group showed no significant changes on cFMA scores. Ashworth scores and EMG activity in both groups increased from Post1 to Post2. Moreover, fMRI-BOLD laterality index showed no significant difference from Pre or Post1 to Post2 sessions.

Conclusions. BMI-based rehabilitation promotes long-lasting improvements in motor function of chronic stroke patients with severe paresis and represents a promising strategy in severe stroke neurorehabilitation.

 

via Brain-Machine Interface in Chronic Stroke: Randomized Trial Long-Term Follow-up – Ander Ramos-Murguialday, Marco R. Curado, Doris Broetz, Özge Yilmaz, Fabricio L. Brasil, Giulia Liberati, Eliana Garcia-Cossio, Woosang Cho, Andrea Caria, Leonardo G. Cohen, Niels Birbaumer, 2019

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[ARTICLE] Effect of Specific Over Nonspecific VR-Based Rehabilitation on Poststroke Motor Recovery: A Systematic Meta-analysis – Full Text

Background. Despite the rise of virtual reality (VR)-based interventions in stroke rehabilitation over the past decade, no consensus has been reached on its efficacy. This ostensibly puzzling outcome might not be that surprising given that VR is intrinsically neutral to its use—that is, an intervention is effective because of its ability to mobilize recovery mechanisms, not its technology. As VR systems specifically built for rehabilitation might capitalize better on the advantages of technology to implement neuroscientifically grounded protocols, they might be more effective than those designed for recreational gaming.

Objective. We evaluate the efficacy of specific VR (SVR) and nonspecific VR (NSVR) systems for rehabilitating upper-limb function and activity after stroke. Methods. We conducted a systematic search for randomized controlled trials with adult stroke patients to analyze the effect of SVR or NSVR systems versus conventional therapy (CT).

Results. We identified 30 studies including 1473 patients. SVR showed a significant impact on body function (standardized mean difference [SMD] = 0.23; 95% CI = 0.10 to 0.36; P = .0007) versus CT, whereas NSVR did not (SMD = 0.16; 95% CI = −0.14 to 0.47; P = .30). This result was replicated in activity measures.

Conclusions. Our results suggest that SVR systems are more beneficial than CT for upper-limb recovery, whereas NSVR systems are not. Additionally, we identified 6 principles of neurorehabilitation that are shared across SVR systems and are possibly responsible for their positive effect. These findings may disambiguate the contradictory results found in the current literature.

Better medical treatments in the acute phase after stroke have increased survival and with that the number of patients needing rehabilitation with an associated increased burden on the health care system.1 Novel technologies have sought to meet this increased rehabilitation demand and to potentially allow patients to continue rehabilitation at home after they leave the hospital.2 Also, technology has the potential to gather massive and detailed data (eg, kinematic and performance data) that might be useful in understanding recovery after stroke better, improving the quality of diagnostic tools and developing more successful treatment approaches.3 Given these promises, several studies and meta-analyses have evaluated the effectiveness of technologies that use virtual reality (VR) in stroke rehabilitation. In a first review, Crosbie et al4 analyzed 6 studies that used VR to provide upper-limb rehabilitation. Although they found a positive effect, they concluded that the evidence was only weak to moderate given the low quality of the research. A later meta-analysis analyzing 5 randomized controlled trials (RCTs) and 7 observational studies suggested a positive effect on a patient’s upper-limb function after training.5 Another meta-analysis of 26 studies by Lohse et al,6 which compared specific VR (SVR) systems with commercial VR games, found a significant benefit for SVR systems as compared with conventional therapy (CT) in both body function and activity but not between the 2 types of systems. This study, however, included a variety of systems that would treat upper-limb, lower-limb, and cognitive deficits. Saywell et al7 analyzed 30 “play-based” interventions, such as VR systems including commercial gaming consoles, rehabilitation tools, and robot-assisted systems. They found a significant effect of play-based versus control interventions in dose-matched studies in the Fugl-Meyer Assessment of the Upper Extremity (FM-UE).7 In contrast, a more recent large-scale analysis of a study with Nintendo Wii–based video games, including 121 patients concluded that recreational activities are as effective as VR.8A later review evaluated 22 randomized and quasi–randomized controlled studies and concluded that there is no evidence that the use of VR and interactive video gaming is more beneficial in improving arm function than CT.9 In all, 31% of the included studies tested nonspecific VR (NSVR) systems (Nintendo Wii, Microsoft Xbox Kinect, Sony PlayStation EyeToy). Hence, although VR-based interventions have been in use for almost 2 decades, their benefit for functional recovery, especially for the upper limb, remains unknown. Possibly, these contradictory results indicate that, at present, studies are too few or too small and/or the recruited participants too variable to be conclusive.10 However, alternative conclusions can be drawn. First, VR is an umbrella term. Studies comparing its impact often include heterogeneous systems or technologies, customized or noncustomized for stroke treatment, addressing a broad range of disabilities. However, effectiveness can only be investigated if similar systems that rehabilitate the same impairment are contrasted. This has been achieved by meta-analyses that investigated VR-based interventions for the lower limb, concluding that VR systems are more effective in improving balance or gait than CT.11Second, a clear understanding of the “active ingredients”3 that should make VR interventions effective in promoting recovery is missing. Therapeutic advantages of VR identified in current meta-analyses are that it might apply principles relevant to neuroplasticity,5,9 such as providing goal-oriented tasks,5,9 increasing repetition and dosage,5,9 providing therapists and patients with additional feedback,5,6,9 and allowing to adjust task difficulty.6 In addition, it has been suggested that the use of VR increases patient motivation,6 enjoyment,8,9 and engagement7; makes intensive task-relevant training more interesting4,7; and offers enriched environments.9 Although motivational aspects are important in the rehabilitation process because they possibly increase adherence,3 their contribution to recovery is difficult to quantify because it relies on patients’ subjective evaluation.7,1215 Rehabilitation methods, whether VR or not, however, need to be objectively beneficial in increasing the patient’s functional ability. Hence, an enormous effort has been expended to identify principles of neurorehabilitation that enhance motor learning and recovery.1624 Consequently, an effective VR system should besides be motivating, also augment CT by applying these principles in the design.23 Following this argument, we advance the hypothesis that custom-made VR rehabilitation systems might have incorporated these principles, unlike off-the-shelf VR tools, because they were created for recreational purposes. Combining the effects of both approaches in one analysis might, thus, mask their real impact on recovery. Again, in the rehabilitation of the lower limb, this effect has been observed. Two meta-analyses investigating the effect of using commercial VR systems for gait and balance training did not find a superior effect, which contradicts the conclusions of the other systematic reviews.11 In upper-limb rehabilitation, this question has not been properly addressed until the most recent review by Aminov et al.25 However, there are several flaws in the method applied that could invalidate the results they found. Specifically, studies were included regardless of their quality, and it is not clear which outcome measurements were taken for the analysis according to the World Health Organization’s International Classification of Function, Disability, and Health (ICF-WHO).26 In addition, a specifically designed rehabilitation system (Interactive Rehabilitation Exercise [IREX])27 was misclassified as an off-the-shelf VR tool. Because their search concluded in June 2017, the more recent evidence is missing. We decided to address these issues by conducting a well-controlled meta-analysis that focuses only on RCTs that use VR technologies for the recovery of the upper limb after stroke. We analyze the effect of VR systems specifically built for rehabilitation (ie, SVR systems) and off-the-shelf systems (ie, NSVR commercial systems) against CT according to the ICF-WHO categories. Also, we extracted 11 principles of motor learning and recovery from established literature that could act as “active ingredients” in the protocols of effective VR systems. Through a content analysis, we identified which principles are present in the included studies and compared their presence between SVR and NSVR systems. We hypothesized, first, that SVR systems might be more effective than NSVR systems as compared with CT in the recovery of upper-limb movement and, second, that this superior effect might be a result of the specific principles included in SVR systems.

 

This meta-analysis was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines.28

Identification of RCTs

We define VR as a computer-based technology that provides the user with a sense of presence in a virtual environment,29 which is induced by exposing the user to computer-generated sources of sensory stimulation that satisfy their perceptual predictions and expected sensorimotor contingencies.30 The studies included aimed at training the upper extremity of stroke patients through active participation, without assistive robotic devices (eg, exoskeleton, end-effector devices) or exogenous stimulation. We compared the impact on body function and activity of 2 kinds of VR systems with CT: SVR and NSVR systems. SVR systems were developed exclusively for neurorehabilitation purposes. NSVR systems, on the other hand, are recreational and/or off-the-shelf video games (eg, Nintendo Wii, Microsoft Xbox). As CT, we considered occupational therapy and physical therapy. To identify all RCTs in these 2 categories, we performed a computerized search in the bibliographic databases MEDLINE (OVID), Cochrane Library Plus (including EMBASE), CINAHL, APA PsycNET, DARE, and PEDro for studies that were published in English from inception until August 7, 2018, the day of the conclusion of the search. The search strategy (Supplementary Table 1) included only RCTs that tested the efficacy of SVR or NSVR systems in recovering the upper limbs of stroke patients who were either in the acute (up to 21 days poststroke), subacute (between 3 weeks and 3 months poststroke), or chronic (after 3 months poststroke) stage. We combined the effects of various chronicity bands because the current literature suggests that principles of motor learning interact constantly with the biological processes of recovery,31 and therefore, no differential effect between SVR and NSVR systems resulting from chronicity should be expected. This notion has also been confirmed by the latest meta-analysis.25 In addition, splitting the identified literature into VR type, ICF-WHO category, and chronicity reduces statistical power because of the small number of studies remaining in each band. Two reviewers (BRB and MM) assessed the studies for eligibility. We excluded studies that were not carried out on humans, lacked a control group, included less than 5 participants per experimental condition, did not target upper-extremity rehabilitation, used exoskeletons as interfaces, used exogenous stimulation (such as transcranial stimulation), or did not provide information on standard clinical scales (Figure 1). Exoskeletons and exogenous stimulation protocol where excluded for the passive or active support provided in the rehabilitation process that might lead to different outcomes.

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Figure 1. Study flow diagram (PRISMA). The selection process of identified randomized controlled trials.

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Continue —>  Effect of Specific Over Nonspecific VR-Based Rehabilitation on Poststroke Motor Recovery: A Systematic Meta-analysis – Martina Maier, Belén Rubio Ballester, Armin Duff, Esther Duarte Oller, Paul F. M. J. Verschure, 2019

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[Abstract] Improving walking ability in people with neurological conditions: A theoretical framework for biomechanics driven exercise prescription

Abstract

The purpose of this paper is to discuss how knowledge of the biomechanics of walking can be used to inform the prescription of resistance exercises for people with mobility limitations. Muscle weakness is a key physical impairment that limits walking in commonly occurring neurological conditions such as cerebral palsy, traumatic brain injury and stroke. Few randomised trials to date have shown conclusively that strength training improves walking in people living with these conditions. This appears to be because

1) the most important muscle groups for forward propulsion when walking have not been targeted for strengthening, and

2) strength training protocols have focused on slow and heavy resistance exercises, which do not improve the fast muscle contractions required for walking.

We propose a theoretical framework to improve exercise prescription by integrating the biomechanics of walking with the principles of strength training outlined by the American College of Sports Medicine (ACSM), to prescribe exercises that are specific to improving the task of walking. The high angular velocities that occur in the lower limb joints during walking indicate that resistance exercises targeting power generation would be most appropriate. Therefore, we propose the prescription of plyometric and ballistic resistance exercise, applied using the ACSM guidelines for task-specificity, once people with neurological conditions are ambulating, to improve walking outcomes. This new theoretical framework for resistance training ensures that exercise prescription matches how the muscles work during walking.

via Improving walking ability in people with neurological conditions: A theoretical framework for biomechanics driven exercise prescription – Archives of Physical Medicine and Rehabilitation

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[ARTICLE] Rehabilitation of Motor Function after Stroke: A Multiple Systematic Review Focused on Techniques to Stimulate Upper Extremity Recovery – Full Text

Associated Data

Supplementary Materials

Abstract

Stroke is one of the leading causes for disability worldwide. Motor function deficits due to stroke affect the patients’ mobility, their limitation in daily life activities, their participation in society and their odds of returning to professional activities. All of these factors contribute to a low overall quality of life. Rehabilitation training is the most effective way to reduce motor impairments in stroke patients. This multiple systematic review focuses both on standard treatment methods and on innovating rehabilitation techniques used to promote upper extremity motor function in stroke patients. A total number of 5712 publications on stroke rehabilitation was systematically reviewed for relevance and quality with regards to upper extremity motor outcome. This procedure yielded 270 publications corresponding to the inclusion criteria of the systematic review. Recent technology-based interventions in stroke rehabilitation including non-invasive brain stimulation, robot-assisted training, and virtual reality immersion are addressed. Finally, a decisional tree based on evidence from the literature and characteristics of stroke patients is proposed. At present, the stroke rehabilitation field faces the challenge to tailor evidence-based treatment strategies to the needs of the individual stroke patient. Interventions can be combined in order to achieve the maximal motor function recovery for each patient. Though the efficacy of some interventions may be under debate, motor skill learning, and some new technological approaches give promising outcome prognosis in stroke motor rehabilitation.

Introduction

The World Health Organization (WHO) estimates that stroke events in EU countries are likely to increase by 30% between 2000 and 2025 (Truelsen et al., ). The most common deficit after stroke is hemiparesis of the contralateral upper limb, with more than 80% of stroke patients experiencing this condition acutely and more than 40% chronically (Cramer et al., ). Common manifestations of upper extremity motor impairment include muscle weakness or contracture, changes in muscle tone, joint laxity, and impaired motor control. These impairments induce disabilities in common activities such as reaching, picking up objects, and holding onto objects (for a review on precision grip deficits, see Bleyenheuft and Gordon, ).

Motor paresis of the upper extremity may be associated with other neurological manifestations that affect the recovery of motor function and thus require focused therapeutic intervention. Deficits in somatic sensations (body senses such as touch, temperature, pain, and proprioception) after stroke are common with prevalence rates variously reported to be 11–85% (Carey et al., ; Yekutiel, ; Hunter, ). Functionally, the motor problems resulting from sensory deficits after stroke can be summarized as (1) impaired detection of sensory information, (2) disturbed motor tasks performance requiring somatosensory information, and (3) diminished upper extremity rehabilitation outcomes (Hunter, ). Sensation is essential for safety even if there is adequate motor recovery (Yekutiel, ). Also, up to 50% of patients experience pain of the upper extremity during the first year after stroke, especially shoulder pain and complex regional pain syndrome-type I (CRPS-type I), which may impede adequate early rehabilitation (Jönsson et al., ; Kocabas et al., ; Sackley et al., ; Lundström et al., ). Furthermore, joint subluxation and muscle contractures can lead to nociceptive musculoskeletal pain (de Oliveira et al., ). Among other complications of stroke the neglect syndrome (Ringman et al., ) and spasticity (Sommerfeld et al., ; Welmer et al., ) affect motor and functional outcomes.

The neurological recovery after stroke displays a nonlinear, logarithmic pattern (Figure (Figure1;1; Kwakkel et al., ; Langhorne et al., ). The greater part of recovery is reported to take place in the first 3 months following stroke (Wade et al., ). However, there is evidence that recovery is not limited to this time period; hand and upper extremity recovery has been reported many years after stroke (Carey et al., ; Yekutiel and Guttman, ). Improvement probably occurs through a complex combination of spontaneous and learning-dependent processes including: restitution, substitution, and compensation (Kwakkel et al., ; Langhorne et al., ). Until the third month after stroke onset, a variable spontaneous neurological recovery can be considered a confounder of rehabilitation intervention (Kwakkel et al., ). In the past, the observation of spontaneous recovery after stroke has misled some authors to believe that recovery of upper extremity function is intrinsic and that little can be done by therapists to influence it (Wade et al., ; Heller et al., ). Progresses in functional outcome appearing after 3 months seem largely dependent on learning adaptation strategies (Kwakkel et al., ). Evidence suggests that neurological repair through brain reorganization supporting true recovery or, alternatively through compensation, may also take place in the subacute and chronic phase after stroke (Krakauer, ).

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Figure 1
Hypothetical pattern of recovery after stroke with timing of intervention strategies. The neurological recovery after stroke displays a nonlinear, logarithmic pattern. The greater part of recovery is reported to take place in the first three months following stroke. Rehabilitation interventions targeting at improving a stroke patients’ performance should be implemented according to the phase of neurological recovery. Reprinted from Langhorne et al. (), Copyright [2011] by Elsevier. Reprinted with permission.

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Continue —> Rehabilitation of Motor Function after Stroke: A Multiple Systematic Review Focused on Techniques to Stimulate Upper Extremity Recovery

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