Posts Tagged paresis

[ARTICLE] Virtual reality-based treatment for regaining upper extremity function induces cortex grey matter changes in persons with acquired brain injury – Full Text



Individuals with acquired brain injuries (ABI) are in need of neurorehabilitation and neurorepair. Virtual anatomical interactivity (VAI) presents a digital game-like format in which ABI survivors with upper limb paresis use an unaffected limb to control a standard input device and a commonplace computer mouse to control virtual limb movements and tasks in a virtual world.


In a prospective cohort study, 35 ambulatory survivors of ABI (25/71% stroke, 10/29% traumatic brain injury) were enrolled. The subjects were divided into three groups: group A received VAI therapy only, group B received VAI and physical/occupational therapy (P/OT), and group C received P/OT only. Motor skills were evaluated by muscle strength (hand key pinch strength, grasp, and three-jaw chuck pinch) and active range of motion (AROM) of the shoulder, elbow, and wrist. Changes were analyzed by ANOVA, ANCOVA, and one-tailed Pearson correlation analysis. MRI data was acquired for group A, and volumetric changes in grey matter were analyzed using voxel-based morphometry (VBM) and correlated with quantified motor skills.


AROM of the shoulder, elbow, and wrist improved in all three groups. VBM revealed grey matter increases in five brain areas: the tail of the hippocampus, the left caudate, the rostral cingulate zone, the depth of the central sulcus, and the visual cortex. A positive correlation between the grey matter volumes in three cortical regions (motor and premotor and supplementary motor areas) and motor test results (power and AROM) was detected.


Our findings suggest that the VAI rehabilitation program significantly improved motor function and skills in the affected upper extremities of subjects with acquired brain injuries. Significant increases in grey matter volume in the motor and premotor regions of affected hemisphere and correlations of motor skills and volume in nonaffected brain regions were present, suggesting marked changes in structural brain plasticity.


Neurological disorders, including acquired brain injuries (ABIs) are important causes of disability and death worldwide [12]. Although age-standardized mortality rates for ischemic and hemorrhagic strokes have decreased in the past two decades, the absolute number of stroke survivors is increasing, with most of the burden in low- and middle-income countries [3]. Another major issue is that trends toward increasing stroke incidence at younger ages has been observed [4]. Moreover, this type of ABI is the leading cause of long-term disability in the United States, with an estimated incidence of 795,000 strokes yearly [2].

In more than 80% of stroke survivors, impairments are seen in at least one of the upper limbs. Six months after a stroke, 38% of patients recover some dexterity in the paretic arm, though only 12% recover substantial function even in spite of having received physical/occupational therapy (P/OT) [5]. Only a few survivors are able to regain some useful function of the upper limb. Failing to achieve useful function has highly negative impacts on the performance of daily living activities [67]. Regaining control and improving upper limb motor function after ABIs are therefore crucial goals of motor system rehabilitation. In left-sided limb impairment, neglect syndrome can contribute to a worsened clinical state, making the alleviation of symptoms even more difficult to achieve. Mirror therapy has been reported as a promising approach to improve neglect symptoms [89].

MRI has been used to track changes in brain connectivity related to rehabilitation [10], and several studies of healthy individuals playing off-the-shelf video games have demonstrated changes in the human brain resulting from interactions in a virtual world (VW) [1112]. Furthermore, playing video games results in brain changes associated with regaining improved, purposeful physical movements [1314]. The socio-cultural relevance of virtual reality (VR) and VW applications lies, more generally, in the fact that these technologies offer interactive environments to users. These interactive environments are actually present in the users’ experiences while less so in the world they share as biological creatures [15]. The way in which we engage with VWs allows for rehabilitation exercises and activities that feel similar to their actual physical world counterparts [11]. In the past two decades, researchers have demonstrated the potential for the interactive experiences of VWs to provide engaging, motivating, less physically demanding, and effective environments for ABI rehabilitation [916,17,18].

One of the suitable rehabilitation methods seems to be exercises and tasks in VW called virtual anatomical interactivity (VAI) [19]. This method provides sensory stimulation / afferent feedback and allows the independent control of an anatomically realistic virtual upper extremity capable of simulating human movements with a true range of motion. ABI survivors are able to relearn purposeful physical movements and regain movement in their disabled upper extremities [19]. Contrary to conventional therapy, which exercises impaired upper limbs to improve limb movement, the general VAI hypothesis is that brain exercises alone (or combined with traditional therapy) may positively influence neuroplastic functions. In the VW, subjects can move their virtual impaired limbs using their healthy hands, meaning simulated physical movements are survivor-authored. Virtual visuomotor feedback may help regain functional connectivity between the brain and the impaired limb, therefore also regaining voluntary control of the limb.

The aim of the study was to test if the shoulder, elbow, and wrist movement; hand pinch strength; and grip strength of the paretic side improved through the use of VAI exclusively or combined with P/OT for upper extremities and how these approaches improved functional outcomes measured by the Action Reach Arm Test [20]. The relationship between changes in abilities to control upper extremities and volumetric changes in cortex grey matter measured by VBM and using MRI was also explored.[…]

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Examples of VAI games: multi-finger actions to pick up a spoon and drop it into a cup, tapping actions using the index and middle fingers on a remote control, removing a light bulb and reinserting it into another fixture designated by a letter of the alphabet, choosing letters of the alphabet to form words and phrases. All actions are performed by clicking and draging mouse on the appropriate body part

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[Case Study] Constraint-Induced Movement Therapy for Improving Motor Function of the Paretic Lower Extremity After Stroke – Abstract


A 56-yr-old woman with chronic stroke and gait dysfunction was recruited for this study. A lower-extremity constraint-induced movement therapy protocol was given consisting of 3.5 hrs/d of supervised intervention activities on 10 consecutive weekdays. Motor training was intensive and involved shaping. In addition, a group of behavior management strategies was used to induce further unsupervised practice and transference of motor skills from the laboratory to real-world situations. Changes in functional mobility, walking speed, balance, level of assistance, perceived quality of movement, and level of confidence while performing daily activities were assessed five times in both the baseline and intervention phases. The outcomes observed after the intervention were determined by calculating the difference between the average scores obtained in both phases. Changes in perceived quality of movement, level of confidence, level of assistance, and balance were observed.

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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.


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] Improving Walking Ability in People With Neurologic Conditions: A Theoretical Framework for Biomechanics-Driven Exercise Prescription.


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 neurologic conditions such as cerebral palsy, traumatic brain injury, and stroke. Few randomized 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 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 American College of Sports Medicine guidelines for task specificity, once people with neurologic 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 Neurologic Conditions: A Theoretical Framework for Biomechanics-Driven Exercise Prescription. – PubMed – NCBI

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[Abstract] Effectiveness of Virtual Reality- and Gaming-Based Interventions for Upper Extremity Rehabilitation Post-Stroke: A Meta-Analysis



To investigate the efficacy of virtual reality (VR)- and gaming-based interventions for improving upper extremity function post-stroke, and to examine demographic and treatment-related factors that may moderate treatment response.

Data Sources

A comprehensive search was conducted within the PubMed, CINAHL/EBSCO, SCOPUS, Ovid MEDLINE and EMBASE databases for articles published between 2005 and 2019 (PROSPERO Registration number 95052).

Study Selection

Articles investigating gaming and VR methods of treatment for upper extremity weakness were collected with the following study inclusion criteria: 1) participants aged 18 or older with upper extremity deficits, 2) randomized controlled trials or prospective study design, 3) Downs-Black rating score of >= 18, and 4) outcome measure was the Wolf Motor Functioning Test (WMFT), the Fugl-Meyer (FM) or the Action Research Arm Test (ARAT).

Data Extraction

Thirty-eight articles met inclusion criteria. The primary outcome was proportional improvement on the WMFT, FM, or ARAT. The following individual or treatment factors were extracted: VR/gaming dose, total treatment dose, chronicity (> or < 6 months), severity of motor impairment, and presence of a gaming component.

Data analysis

Random effects meta-analysis models were utilized to quantify 1) the proportional recovery that occurs following VR/gaming, 2) the comparative treatment effect of VR/gaming versus conventional physiotherapy, and 3) whether the benefit of virtual reality differed based on participant characteristics or elements of the treatment.


On average, VR/gaming interventions produced an improvement of 28.5% of the maximal possible improvement. Dose and severity of motor impairment did not significantly influence rehabilitation outcomes. Treatment gains were significantly larger overall (10.8%) when the computerized training involved a gaming component versus just visual feedback. VR/gaming interventions showed a significant treatment advantage (10.4%) over active control treatments.


Overall, VR/gaming-based upper extremity rehabilitation post-stroke appears to be more effective than conventional methods. Further in-depth study of variables impacting improvement, such as individual motor presentation, treatment dose, and the relationship between the two, are needed.

via Effectiveness of Virtual Reality- and Gaming-Based Interventions for Upper Extremity Rehabilitation Post-Stroke: A Meta-Analysis – ScienceDirect

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[ARTICLE] The effect of aquatic and treadmill exercise in individuals with chronic stroke – Full Text


We compared the effect of gait training on treadmill versus deep water on balance and gait in 12 ischemic stroke chronic survivors randomly sorted to the Pool or Treadmill Groups. Berg Scale (BBS) and timed up and go test (TUG) were applied before and after the interventions. Just one person applied all tests and she was blinded for the aims of the study. Surface EMG of the paretic and non-paretic (NP) side muscles were recorded during walking on a treadmill. Three 100-ms epochs were extracted from the EMG related to gait phases: weight acceptance; propulsion; and pre-strike. For each epoch, we calculated the RMS of the EMG signal. Participants did gait training for 9 weeks (3 times/week, 40 minutes/session). The Pool group did the deep-water walking with a swimming belt. The Treadmill group walked on the treadmill at the maximum speed they could stand. The Manova group compared the effect of training, group, side, muscles, and gait phase into the EMG. Anova was used to test the effect of training, group side, and gait phase into BBS, TUG and EMG variables. Pool and Treadmill had increased balance and agility. The highest EMG RMS occurred at the paretic side, for the Treadmill and after training. The mm. tibialis anterior, gastrocnemius lateralis, vastus lateralis, and biceps femoris presented the highest RMS for the NP side; while for mm. rectus femoris and semitendinosus, the paretic side presented the highest RMS. Thus, the both types of exercise lead to similar functional adaptations with different muscular activations during walking.


Stroke is the second most common cause of death worldwide and the primary cause of chronic disability in adults1), (2. Without intense rehabilitation during the early days after the stroke, neural injuries gradually develop more pronounced motor impairments due to muscle weakness, spasticity and coordination loss3. Later, stroke survivors with chronic impairment become less independent to perform daily life activities, have less social interaction and are more concerned about their future4. Such dependent person with less social life can be considered as having lost motivation. This deprivation occurs because chronic stroke survivors have small resistance to fatigue4)- (6. They do not feel motivated to move continuously or for long periods since they get easily fatigued; as such, rehabilitation programs for such population should spare their activities between motor rehabilitation and increase in physical fitness in order to increase their resistance to fatigue.

In fact, about 80% of stroke survivors can walk without assistance; but their slow walk constrains their daily life activities7), (8. Walking speed is an important outcome for performance evaluation and for functional evaluation in stroke9), (10. The slow walking is due to the lower limb muscles spasticity11)- (14, muscle weakness, postural imbalance and fear of falling. Those clinical impairments also change the gait biomechanics15), (16, inducing asymmetrical, stereotyped and low ranged compensatory movements17. At the early stage of the rehabilitation program, efforts should be addressed to improve body functions in enhance resistance to fatigue.

The aerobic training applied to stroke people enhances physical ability and improves life independence and quality, reducing morbidity and mortality18. Standard aerobic training is usually developed with walking and running. Treadmill protocols to stroke people can recover impaired gait, improve gait parameters and reduce walking asymmetries19. On the other hand, water walking enhances the afferent sensory inflow and improves peak aerobic capacity and walking endurance, being able to affect gait kinematics in patients with stroke18), (20)- (22. It is not clear whether walking on water would provide the same or more benefits compared with the standard treadmill walking for chronic stroke people. In fact, little information is available to support a rehabilitation program for chronic stroke people with reduced mobility. The aim of this study was to compare the effect of aerobic training treadmill versus aerobic training in water for balance and gait in chronic stroke people. We expect that standard treadmill walking training and water walking training will not have similar biomechanical and functional results; therefore, both types of walking training will lead to similar functional results, but the electrical activity of lower limbs will show different behavior after training. Our first hypothesis is that treadmill gait training and deep-water gait training will lead to similar functional adaptations. Our second hypothesis is that treadmill gait training and deep-water gait training will induce different muscle adaptations that will provide different kinds of muscle activation during the walking test. We believe that training will improve participants’ overall fitness, but training specificity will lead to differing muscle activation during the gait test.[…]

Continue —–>  The effect of aquatic and treadmill exercise in individuals with chronic stroke

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[ARTICLE] Mechanisms Of Functional Adaptation Of Post Stroke Patients During Upper Limb Rehabilitation – Full Text


Task oriented approach training of the patient with the arm weight unloading with feedback through the mirror.

Figure 1. Arm weight support training

Stroke is a leading cause of disability of the adult population worldwide. Successful recovery of upper limb motor function occurs only in 20% of cases [1]. Upper limb motor recovery is a most challenging goal, due to lack of patient’s motivation, training intensity and pathological synergy which is very difficult to correct using traditional methods. Poststroke upper limb paresis, spasticity and caused by them pathological synergies is the main problem on the way to daily living activities recovery. The problem of pathological synergies correction and transformation in rehabilitation practice are linked with the complexity of the required motor training approach [2]. A combination of cost-efficient, task-oriented, isolated and complex movement training with biofeedback is required to make synergy a compensatory mechanism for daily activities instead of pathological synkinesia.A promising but insufficiently studied method is virtual reality (VR), as well as its combination with other techniques like arm weight support training. Motor training in virtual reality (VR) with arm weight support creates the necessary facilitated environment for motor skills relearning [3].


45 patients (27 males and 18 females) with medium age 55 [45;65] years were enrolled in this study. All patients had one supratentorial lesion due to ischemic or hemorrhagic stroke (confirmed by MRI). Medium stroke age was 7 [4;12] months. All patients had moderate to severe upper limb paresis measured by Medical Research Council Scale for Muscle Strength and Fugl-Meyer assessment of physical performance (FMAS) upper extremity subscore 45 [35;55]. All patients received 2 weeks of a rehabilitation course, 5 days per week, 45 minutes daily.

Upper limb exoskeleton with weight support system and functional tasks in virtual environment.

Figure 2. Virtual reality with arm weight support training

Main group (n=25)  received 10 training sessions 45  minutes each on Armeo Spring system with separately adjusted weight support for shoulder and forearm and VR imitation of daily living activities such as reaching and grasping. The session includes 10 games like exercises and consistent increase of degrees of freedom from shoulder to the wrist. This condition allows teaching the patient voluntarily prevent pathologic synergy while performing a motor task.

The control group (n=20) received conventional therapy sessions with arm weight support (a system of pulleys), visual feedback (via mirror) and comparable set of tasks – reaching, grasping, manipulating objects.

The reaching test paradigm for motion analysis.

Figure 3. The reaching test.

For primary outcome assessment was used Fugl-Meyer assessment scale for upper limb, Action Research Arm Test (ARAT), Ashworth scale and Frenchay arm test. For motion analysis was used Russian Motion Capture System (Biosoft 3D). The paradigm for biomechanical analysis was presented with the functional reaching test. The reaching test was performed before and after the training course. Sitting at the table patient had to reach and grasp an empty glass located in front of him on the distance of extended healthy arm. For primary outcome were chosen reaching trajectory and arm kinematics, but patients were instructed to focus on the grasping movement to keep reaching movement more automatic. Normal reaching pattern was investigated on 10 healthy volunteers.


FM and ARAT results on the main and control group before and after rehabilitation course.FM and ARAT results on the main and control group before and after rehabilitation course.
Figure 4. FM and ARAT scales before and after rehabilitation.
Table 1. Time of reaching test.
  Before rehabilitation After rehabilitation p-level
Moderate paresis, Ме [25%;75%] 1,5 [1,24; 1,71] 1,26 [0,9; 1,62] p=0,045
Severe paresis, Ме [25%;75%] 2,25 [1,65; 3,76] 2,66 [1,11; 3,05] p=0,043
Normal, Ме [25%;75%] 0,96 [0,87; 1,16]

In our study, the clinical assessment (FM and ARAT scales) showed that paretic hand recovery was found more in patients with moderate and severe paresis. Statistically significant improvements in the arm motor function (FMAS) were found in both groups. However, subsection analysis revealed that the patients of the main group compared to the control group had a more significant improvement in wrist movements. In ARAT was found that in patients with moderate paresis significant improvements occur in both main and control groups. In patients with severe paresis, improvements were observed only in the main group.

However, after motion analysis, a different stereotype of movement recovery was found in different groups of patients. In patients with severe paresis, an increase in the deviation of the movement pattern from the physiological movement was observed. At the same time, the normalization of the motor pattern was noted in patients with moderate paresis.

Table 2. Kinematics parameters in sever hand paresis.
Movement Before rehabilitation, Ме [25%;75%] After rehabilitation, Ме [25%;75%] p-level
Elbow extension 124 [116;126] 112 [109; 125] 0,01
Shoulder  flexion 36 [27; 41] 21 [20; 32] 0,02
Shoulder abduction 10 [10; 17] 19 [18; 22] 0,04
Velocity shoulder abduction 17 [13; 20] 48 [39; 65] 0,02
Velocity elbow extension 39 [26; 69] 29 [18,39] 0,02

The time of reaching test execution in patients with severe paresis after rehabilitation was longer than before and exceeded the normal time more than twice. Curiously,  these changes in patients with severe paresis were associated with an increase in functionality in the paretic arm (p>0,05).

The kinematic parameters such as elbow extension, shoulder abduction and angular velocity in shoulder and elbow joints after rehabilitation were worsened. After a rehabilitation course was founded decreasing of the angular velocity of the elbow joint extension, increasing of the angular velocity of the shoulder joint, decreasing of the flexion in the shoulder joint and angular speed of the elbow joint extension.

The analysis of trunk movements in severe paresis patients was shown that after rehabilitation course the trunk compensatory strategy was increased (trunk was mowed forward when patient reach the glass). These changes were associated with an increase in functionality in the paretic arm (p>0,05).


Table 3. Body displacement in reaching test.
Shoulder displacement Before rehabilitation, Ме [25%;75%] After rehabilitation, Ме [25%;75%]
Healthy shoulder 23 [19,8; 57,44] 66 [49;81]
Paretic shoulder 169 [88; 178] 215 [162; 229]

If we summarized data of clinical and biomechanical parameters we see, that patients with severe paresis formed the new compensatory strategy of motion. Because of the significant changes in functional recovery are combined with worsened of biomechanical parameters.

It is believed that it is the resistance to pathological synergies and the forced training in physiological movement is the most effective method. However, correction of pathological synergies allows developing the most energy-efficient stereotype of movements for patients with regard to their individual capabilities. Combined VR and weight support training can be more effective to restore the impaired motor function after stroke than conventional weight support training. This approach contributes to the motor pattern reorganization through biomechanical and visual feedback, projected into the virtual space.


[1] Beebe J.A., Lang C.E. Active range of motion predicts upper extremity function 3 months after stroke. Stroke. 2009 40 (5): 1772–1779.

[2] Cirstea M.C., Levin M.F. Compensatory strategies for reaching in stroke. Brain. 2000 123 (5): 940–953.

[3] Laver K.E., George S.,J.E. Thomas, M. Deutsch. Crotty Virtual reality for stroke rehabilitation. Cochrane Database Syst Rev.  2015 12 (2): 83.

via Mechanisms Of Functional Adaptation Of Post Stroke Patients During Upper Limb Rehabilitation.

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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. 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. 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. 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 al 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. Another meta-analysis of 26 studies by Lohse et al, 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 al 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). 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. A 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. 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. 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. Second, a clear understanding of the “active ingredients” 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,, such as providing goal-oriented tasks,, increasing repetition and dosage,, providing therapists and patients with additional feedback,,, and allowing to adjust task difficulty. In addition, it has been suggested that the use of VR increases patient motivation, enjoyment,, and engagement; makes intensive task-relevant training more interesting,; and offers enriched environments. Although motivational aspects are important in the rehabilitation process because they possibly increase adherence, their contribution to recovery is difficult to quantify because it relies on patients’ subjective evaluation., 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. Consequently, an effective VR system should besides be motivating, also augment CT by applying these principles in the design. 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. In upper-limb rehabilitation, this question has not been properly addressed until the most recent review by Aminov et al. 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). In addition, a specifically designed rehabilitation system (Interactive Rehabilitation Exercise [IREX]) 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.[…]


Continue —->  Effect of Specific Over Nonspecific VR-Based Rehabilitation on Poststroke Motor Recovery: A Systematic Meta-analysis

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



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.


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.


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.


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.


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



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.


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.


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.


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.


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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