Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Domiciliary VR-Based Therapy for Functional Recovery and Cortical Reorganization: Randomized Controlled Trial in Participants at the Chronic Stage Post Stroke

Domiciliary VR-Based Therapy for Functional Recovery and Cortical Reorganization: Randomized... Background: Most stroke survivors continue to experience motor impairments even after hospital discharge. Virtual reality-based techniques have shown potential for rehabilitative training of these motor impairments. Here we assess the impact of at-home VR-based motor training on functional motor recovery, corticospinal excitability and cortical reorganization. Objective: The aim of this study was to identify the effects of home-based VR-based motor rehabilitation on (1) cortical reorganization, (2) corticospinal tract, and (3) functional recovery after stroke in comparison to home-based occupational therapy. Methods: We conducted a parallel-group, controlled trial to compare the effectiveness of domiciliary VR-based therapy with occupational therapy in inducing motor recovery of the upper extremities. A total of 35 participants with chronic stroke underwent 3 weeks of home-based treatment. A group of subjects was trained using a VR-based system for motor rehabilitation, while the control group followed a conventional therapy. Motor function was evaluated at baseline, after the intervention, and at 12-weeks follow-up. In a subgroup of subjects, we used Navigated Brain Stimulation (NBS) procedures to measure the effect of the interventions on corticospinal excitability and cortical reorganization. Results: Results from the system’s recordings and clinical evaluation showed significantly greater functional recovery for the experimental group when compared with the control group (1.53, SD 2.4 in Chedoke Arm and Hand Activity Inventory). However, functional improvements did not reach clinical significance. After the therapy, physiological measures obtained from a subgroup of subjects revealed an increased corticospinal excitability for distal muscles driven by the pathological hemisphere, that is, abductor pollicis brevis. We also observed a displacement of the centroid of the cortical map for each tested muscle in the damaged hemisphere, which strongly correlated with improvements in clinical scales. Conclusions: These findings suggest that, in chronic stages, remote delivery of customized VR-based motor training promotes functional gains that are accompanied by neuroplastic changes. Trial Registration: International Standard Randomized Controlled Trial Number NCT02699398 (Archived by ClinicalTrials.gov at https://clinicaltrials.gov/ct2/show/NCT02699398?term=NCT02699398&rank=1) (JMIR Serious Games 2017;5(3):e15) doi: 10.2196/games.6773 http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 1 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al KEYWORDS stroke; movement disorder; recovery of function, neuroplasticity; transcranial magnetic stimulation; physical therapy; hemiparesis; computer applications software Participants Introduction Participants were first approached by an occupational therapist After initial hospitalization, many stroke patients return home from the rehabilitation units of Hospital Esperanza and Hospital relatively soon despite still suffering from impairments that Vall d’Hebron from Barcelona to determine their interest in require continuous rehabilitation [1]. Therefore, ¼ to ¾ of participating in a research project. Recruited participants met patients display persistent functional limitations for a period of the following inclusion criteria: (1) mild-to-moderate 3 to 6 months after stroke [2]. Although clinicians may prescribe upper-limbs hemiparesis (Proximal MRC>2) secondary to a a home exercise regimen, reports indicate that only one-third first-ever stroke (>12 months post-stroke), (2) age between 45 of patients actually accomplish it [3]. Consequently, substantial and 85 years old, (3) absence of any major cognitive impairment gains in health-related quality of life during inpatient stroke (Mini-Mental State Evaluation, MMSE>22), and (4) previous rehabilitation may be followed by equally substantial declines experience with RGS in the clinic. The ethics committee of in the 6 months after discharge [4]. Multiple studies have shown, clinical research of the Parc de Salut Mar and Vall d’Hebron however, that supported discharge combined with at home Research Institute approved the experimental guidelines. rehabilitation services does not compromise clinical inpatient Thirty-nine participants at the chronic stage post-stroke were outcomes [5-7] and may enhance recovery in subacute stroke recruited for the study by two occupational therapists, between patients [8]. Hence, it is essential that new approaches are October 2011 and January 2012, and were assigned to a RGS deployed that help to manage chronic conditions associated (n=20) or a control group (n=19) using stratified permuted block with stroke, including domiciliary interventions [9] and the randomization methods for balancing the participants’ augmentation of current rehabilitation approaches in order to demographics and clinical scores at baseline (Table 1). One enhance their efficiency. There should be increased provision participant in the RGS group refused to participate. Prior to the of home-based rehabilitation services for community-based experiment, participants signed informed consent forms. This adults following strok e, taking cost-effectiveness, and a quick trial was not registered at or before the onset of participants’ family and social reintegration into account [10]. enrollment because it is a pilot study that evaluates the feasibility of a prototype device. However, this study was registered One of the latest approaches in rehabilitation science is based retrospectively in ClinicalTrials.gov and has the identifier on the use of robotics and virtual reality (VR), which allow NCT02699398. remote delivery of customized treatment by combining dedicated interface devices with automatized training scenarios [10-12]. Instrumentation Several studies have tested the acceptability of VR-based setups Description of the Rehabilitation Gaming System as an intervention and evaluation tool for rehabilitation [13-15]. The RGS integrates a paradigm of goal-directed action execution One example of this technology is the, so called, Rehabilitation and motor imagery [17], allowing the user to control a virtual Gaming System (RGS) [16], which has been shown to be body (avatar) through an image capture device (Figure 1). For effective in the rehabilitation of the upper extremities in the this study, we developed training and evaluation scenarios within acute and the chronic phases of stroke [13]. However, so far the RGS framework. In the Spheroids training scenario (Figure little work exists on the quantitative assessment of the clinical 1), the user has to perform bilateral reaching movements to impact of VR based approaches and their effects on neural intercept and grasp a maximum number of spheres moving reorganization that can directly inform the design of these towards him [16]. RGS captures only joint flexion and extension systems and their application in the domiciliary context. The and filters out the participant’s trunk movements, therefore main objective of this paper is to further explore the potential preventing the execution of compensatory body movements and limitations of VR technologies in domiciliary settings. [18]. This task was defined by three difficulty parameters, each Specifically, we examine the efficacy of a VR-based therapy of them associated with a specific performance descriptor: (1) when used at home for (1) assessing functional improvement, different trajectories of the spheres require different ranges of (2) facilitating functional recovery of the upper-limbs, and (3) joint motion for elbow and shoulder, (2) the size of the spheres inducing cortical reorganization. This is the first study testing require different hand and grasp precision and perceptual the effects of VR-based therapy on cortical reorganization and abilities, and (3) the velocity of the spheres require different corticospinal integrity using NBS. movement speeds and timing. All these parameters, also including the range of finger flexion and extension required to Methods grasp and release spheroids, were dynamically modulated by Design the RGS Adaptive Difficulty Controller [19] to maintain the performance ratio (ie, successful trials over the total trials) above We conducted a parallel-group, controlled trial in order to 0.6 and below 0.8, optimizing effort and reinforcement during compare the effectiveness of domiciliary VR-based therapy training [20]. versus domiciliary occupational therapy (OT) in inducing functional recovery and cortical reorganization in chronic stroke patients. http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 2 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al Figure 1. Experimental setup and protocol: (A) Movements of the user’s upper limbs are captured and mapped onto an avatar displayed on a screen in first person perspective so that the user sees the movements of the virtual upper extremities. A pair of data gloves equipped with bend sensors captures finger flexion. (B) The Spheroids is divided into three subtasks: hit, grasp, and place. A white separator line divides the workspace in a paretic and non-paretic zone only allowing for ipsilateral movements.(C) The experimental protocol. Evaluation periods (Eval.) indicate clinical evaluations using standard clinical scales and Navigated Brain Stimulation procedures (NBS). These evaluations took place before the first session (W0), after the last session of the treatment (day 15, W3), and at follow-up (week 12, W12). rehabilitation during 5 weekly days, for 3 consecutive weeks. Description of the Evaluation Scenario The RGS group followed a home-based training paradigm based Designing automated evaluation tools to be used at-home in a on the Spheroids scenario (Figure 1), comprising 3 consecutive non-supervised setup could provide objective and frequent subtasks: Hit, Grasp, and Place, with a total duration of 20 measurements of recovery, offering valuable information to minutes, 6 minutes, and 40 seconds each. Participants in the clinicians and primary users, and driving autonomous RGS group completed the Automated Evaluation of Motor rehabilitation technologies. We, therefore, developed the Function once a day, before the training session, which lasted Automated Evaluation of Motor Function (AEMF), a VR-based 2 minutes and 30 seconds. We delivered the system and trained evaluation scenario for the assessment of upper-limb motor the participants and their corresponding caregivers to use the function that was designed to operate under non-supervised system without supervision. The control group performed a 20 conditions. minutes OT task at home, without assistance, which consisted of horizontal and vertical stacking and unstacking of plastic Description of the Automated Evaluation of Motor cups with their right and left hand consecutively. This task was Function (AEMF) designed by an occupational therapist to match the movements In order to assess proximal and distal motor function, the AEMF trained during the RGS task. At the end of the therapy, the scenario is divided into two separated tasks. In task 1, participants reported to have completed a minimum of 1 session participants were asked to perform planar wiping movements a day. In the RGS group, the therapy time was similarly split with their arms to clear a virtual surface covered with small between 10 minutes of activity with the affected hand and 10 cubes. In task 2, participants were instructed to squeeze a virtual minutes with the less affected hand. All participants were asked object by flexing and extending their fingers. In order to to perform a minimum of 1 and a maximum of 3 training guarantee that the AEMF tasks were correctly understood, each sessions a day. of these was first performed using the non-paretic limb and then Outcome Measures with the paretic limb. Participants did not receive any explicit feedback (ie, knowledge of results) about their overall All participants’ motor function was evaluated at day 1, day 15 performance. During task execution, we collected data of hand of the rehabilitation program, and week 12 follow-up (Figure position and joint rotation (fingers, elbows, and shoulders) to 1), using 8 standard clinical scales. Evaluations were carried compute three main performance descriptors: the horizontal out by two occupational therapists who were not blinded to planar area covered, finger flexion, and extension. treatment assignment. Primary outcomes were the improvement in the upper extremity section of the Fugl-Meyer Assessment Experimental Protocol (UE-FM) [21], and the Chedoke Arm and Hand Activity In order to test the effectiveness of VR in the domiciliary Inventory (CAHAI) [22]. Secondary outcomes were context, each participant received daily home-based upper-limb improvements in Barthel Index (BI) [23], Ashworth Scale for http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 3 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al distal (ASd) and proximal upper limb (ASp) [24], Medical synchronized with a three-dimensional tracking system Research Council Scale for distal (MRCd) and proximal upper (Navigated Brain System, Nexstim, Eximia, Finland). Motor limb (MRCp) [25], and grip force. In addition, we used the evoked potentials (MEPs) were recorded using surface Hamilton Scale to assess mood disorders [26], and the Visual electrodes (Ambu, Neuroline 700), connected to a 4 channel Analog Scale (VAS) to evaluate shoulder pain [27]. electromyographic (EMG) system (Key-Point net, Medtronic, USA). Data collected during NBS was analyzed to estimate the Both during the training and evaluation sessions, we captured motor threshold at rest (RMT) for abductor pollicis brevis (APB) the user’s movements and mapped them onto a biomechanical and extensor-carpi radialis (ECR) for each participant. The RMT model of the upper limbs. Specifically, virtual movements were was defined as the intensity of TMS stimulus needed to obtain controlled by the angles of the users’ joints measured by a more than 50% of responses with amplitudes over 50 μV. After motion capture device at 30Hz (Kinect, Microsoft, USA). The finding the RMT of both muscles we proceeded to draw the range of finger flexion was captured by a pair of data gloves cortical maps of both the healthy and pathological hemisphere (DGTech Engineering Solutions, Bazzano, Italy) equipped with in each participant. Maps were drawn at 110% of RMT, a bend sensors, measures range from 0 to 1, indicating maximum percentage commonly used to avoid no-response spots and extension and maximum flexion respectively. suppressive effects. When no-response was found on the Navigated Brain Stimulation (NBS) procedures [28] were used pathological side we incremented the stimulus intensity stepwise to assess training-induced changes in the functional integrity in a logarithmic fashion (ie, 110%, 120%, and 140%) until the of the pyramidal tract and cortical maps in the primary motor maximum stimulator output was reached. To determine the area (M1). A total of 17 participants (3 of them assigned to the boundaries, we stopped searching a particular direction until control group) accepted to participate in the NBS procedure, two no-response points aligned in the same vector and direction which was conducted for each subject before and after treatment or when the sulcus boundaries were reached. After processing (Figure 2). A 3-Tesla magnet (Philips Achieva) was used for the data, we characterized cortical representations of APB and 3D MRI acquisitions. In order to faithfully build a 3D model ECR and corticospinal connectivity in each cerebral hemisphere of the participant’s scalp and parenchyma we used T1W- by estimating the centroid of the cortical motor output map and 3D-TFE acquired sequences comprising a minimum of 178 their corresponding Stimulation Efficacy (SE). SE was the slices. For nTMS mapping we used a butterfly coil (MC-B70, greatest value in the 80th percentile of the MEPs divided by the Medtronic, Alpine, USA), and magnetic stimulation equipment maximum stimulation intensity. (Mag Pro-30 with MagOption, Medtronic, Alpine, USA) Figure 2. Navigated Brain Stimulation (NBS) procedure. Bottom right: axial and coronal view of a magnetic resonance imaging (MRI) scan at the level of the stroke for one of the participants in the experimental group showing a partial anterior circulation infarct due to an embolism. Bottom right: Example of NBS mapped cortical motor representations; colored areas indicate the targeted cortical sites. In order to validate the RGS Adaptive Difficulty Controller, Data Analysis automatic performance ratios and difficulty parameters assigned For statistical analysis, data were tested for normality using the by RGS to the paretic and non-paretic limb were compared Kolmogorov-Smirnov test. To identify significant time effects (Wilcoxon signed-rank test). Next, to explicitly study progress on clinical scores we performed a Friedman test. Next, we in performance, we averaged values for each difficulty parameter conducted a post-hoc analysis using 2-tailed Mann-Whitney U per session and performed a within-subjects time-series analysis tests to compare improvements between groups at week 3 and of the means (Friedman test). week 12 follow-up. Within-subject analysis of recovery was Data of hand position and joint rotation collected during assessed using standard clinical scales (Table 1). We reversed performance in AEMF were filtered using a second order the polarity of Hamilton, VAS and Ashworth scales so that Butter-worth low- pass filter (cut-off at 6 Hz) reducing noise. positive changes on all scales would express recovery. In order to assess the participant’s motor function within AEMF, we calculated three performance descriptors for each extremity: http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 4 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al (1) the work area was defined as the dorsal surface area of the Finally, we compared the Stimulation Efficacy (SE) and the movement space, while (2) finger flexion, and (3) extension centroid location of the cortical motor areas representing APB were defined as the maximal and minimal metacarpal angles and ECR in M1, for the pathological and non-pathological respectively, averaged across all fingers. hemispheres (Wilcoxon sign-sum test). In order to extract training effects, we performed a within-subject analysis of the We tested AEMF sensitivity by examining between-limbs Stimulation Efficacy and the centroid location of the cortical differences in descriptor values (ie, covered area, finger flexion maps in M1 before and after treatment (Wilcoxon sign-sum and finger extension) for each subject (Wilcoxon signed-rank test). We used a Spearman test to study the correlations between test). Next, in order to explore AEMF test-retest stability and NBS outcome measures and improvements in clinical scales. sensitivity to capture improvement, we analyzed changes in descriptor values across sessions (Friedman test). In addition, Two-sided significance level for all statistical tests was defined we studied the relation between standardized clinical scores and as alpha=0.05.Data processing and statistical analysis were AEMF measurements of motor function by computing a performed using Matlab 2013a (MathWorks, Inc.). Due to Spearman correlation coefficient for each descriptor and clinical limited statistical power, we did not correct for multiple scale at the corresponding evaluation period. comparisons. Table 1. Participants’ demographics and scores from clinical scales at baseline. Demographics RGS (n=17) Control (n=18) P value Gender (female), n (%) 9 (53) 12 (67) Age, mean (SD) 65.05 (10.33) 61.75 (12.94) Affected side (left), n (%) 11 (65) 9 (50) Type (hemorrhagic), n (%) 6 (33) 6 (33) c d e a 4/3/4 6/2/4 Oxford class (LA C /PAC /TAC ) .65 Days after strok e, mean (SD) 1073.43 (767.74) 798.06 (421.80) MMSE [ 16], mean (SD) 28.24 (2.33) 28.22 (2.34) Hamilton [ 17], mean (SD) 3.71 (3.35) 4.56 (3.24) Grip force, mean (SD) 6.15 (5.04) 5.94 (5.85) f b 3.47 (0.51) 3.39 (0.61) MRC proximal [ 19], mean (SD) .76 MRC distal [ 19], mean (SD) 2.82 (1.19) 3.17 (0.99) FMA [ 20], mean (SD) 42.94 (14.37) 43.44 (13.48) g b 52.82 (23.10) 53.50 (22.51) CAHAI [21], mean (SD) .95 Barthel [ 22], mean (SD) 89.53 (9.43) 84.72 (14.19) Ashworth proximal [ 23], mean (SD) 1.24 (1.25) 1.22 (1.31) Ashworth distal [ 23], mean (SD) 1.47 (1.51) 1.00 (1.41) h b 1.59 (2.76) 2.61 (2.64) VAS shoulder [ 16], mean (SD) .13 Chi-square test. Wilcoxon rank-sum test. LAC: Lacunar stroke. PAC: Partial anterior circulation stroke. TAC: Total anterior circulation stroke. MRC: Medical Research Council. CAHAI: Chedoke Arm and Hand Activity Inventory (version CAHAI-13). VAS: Visual Analog Scale. http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 5 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al during training. Differences in performance showed a trend Results toward significance in Grasp and Place subtasks (P<.06, Wilcoxon). Notice that in order to provide an optimal training Benefits of At-Home VR-Based Training on Motor challenge for the user, the RGS system dynamically adjusted Recovery the difficulty parameters for each arm, mean performance ratios In order to assess the impact of the RGS treatment, we were maintained around 0.7 for each limb, across all tasks and conducted a repeated measures analysis of the functional sessions. Therefore these differences in performance between recovery captured through standardized clinical scales. Analysis limbs may uncover existing floor effects in the difficulty of participants’ demographics revealed no significant differences adaptation algorithm for those participants unable to achieve between groups at baseline (Table 1). Comparing the change complete power grasp movements [19]. In line with these between baseline and week 3 in clinical scores we detected a findings, a within-subject analysis revealed a significant increase significant difference on the CAHAI scale (Table 2). The RGS in the range and size difficulty coefficients assigned to the group showed significant improvements in CAHAI as compared paretic limb during the Grasp and Place task across sessions to the control group (P=.05, Wilcoxon signed-rank test, Table (P<.05, Friedman). Similar improvements were observed for 2). A post-hoc power analysis was conducted to determine the the non-paretic limb during the Hit and the Grasp subtasks. power of this statistical comparison for the sample size n=17. Automated Evaluation of Motor Function A medium effect size, d=0.48, at alpha=0.05 reached a low power level (Beta=0.4). A within-subjects analysis on the RGS In order to study the RGS AEMF sensitivity, we compared group revealed an average improvement of 1.53 (SD 2.4) points measurements for the paretic and non-paretic limb. In addition, on the CAHAI scale (P=.03, Wilcoxon signed-rank test); we explored the test-retest stability of these parameters. We however, these effects did not persist at the week 12 follow-up observed that estimates of working area and maximal finger evaluation. At follow-up we observed a significant difference extension performed by the paretic limb in AEMF were between groups in improvement on the Ashworth scale only significantly lower when compared to the non-paretic limb for distal muscle groups (P=.03, power=0.6, Wilcoxon (P<.01, Wilcoxon). Within-subjects analysis showed no effect signed-rank test), however, this difference did not reach of time in the work area for the non-paretic (P=.06, Friedman), statistical significance after Bonferroni correction. and a significant effect for the paretic limb (P=.03, Friedman). Post-hoc analysis revealed that these gains occurred during Progress of Performance in VR week 3 (P<.01, Wilcoxon). We also found a significant effect Participants in the RGS group completed a variable total number of time on maximum finger flexion for the paretic limb (P=.006, of Hit (37.1, SD 18.4), Grasp (35.1, SD 17.0) and Place (34.2, Friedman), which occurred at week 2 and 3 (P<.01, Wilcoxon, SD 16.8) subtasks along the 3 weeks of treatment. All patients Figure 3). In order to validate AEMF, we correlated its participating in the study were able to put the gloves on with measurements with assessments from standard clinical scales assistance, and autonomously set-up and use the system until (Table 2). We used AEMF-derived improvement descriptors to finishing the game. In order to assess whether the adaptive fit scores from the CAHAI scale. An optimal fit was achieved difficulty controller effectively provided customized training by the sum of maximal finger flexion and extension intensities that matched the participants’ capabilities, we (R-squared=.602, P<.001). explored inter-limb differences in mean performance ratios Figure 3. A: AEMF captures an improvement in finger flexion during treatment. Averaged movement profile of fingers excursion performed by one subject during one of the sessions. Units of finger flexion are expressed as a ratio of complete flexion. B: Mean changes in maximal finger flexion for all subjects in the RGS group across the three weeks of intervention, for both non-paretic (NPL) and paretic limbs (PL). http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 6 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al Table 2. Effects of RGS treatment versus control on clinical scales within and between groups for the post treatment assessment at week 3 and the long-term follow up at week 12. Assessment RGS (n=17) Control (n=18) Between Groups Effect size Improvement, P Improvement, mean (SD) P P Cohen d mean (SD) End (W eek 3) 0.35 (1.62) .43 1.22 (3.84) .15 .33 −0.30 UE-FM 1.53 (2.4) .01 −0.67 (6.01) .90 .05 0.48 CAHAI Barthel 0.00 (1.87) >.99 1.00 (2.87) .25 .44 −0.41 0.06 (0.24) >.99 0.11 (0.32) .50 .61 −0.17 MRCp 0.06 (0.43) >.99 0.11 (0.47) .63 .74 −0.12 MRCd 0.00 (0.35) >.99 0.06 (0.24) >.99 .32 0.40 Asp 0.12 (0.33) .50 0.00 (0.34) >.99 .32 0.36 Asd Grip force 0.41 (1.78) .89 0.38 (2.65) .47 .57 0.01 Hamilton 0.88 (2.45) .16 0.67 (1.57) .13 .66 0.10 0.41 (1.81) .05 −0.28 (1.90) .69 .63 0.37 VAS-S Follow-up (Week 12) UE-FM −0.18 (3.50) .82 1.39 (3.63) .11 .21 0.34 CAHAI −0.06 (6.51) .74 0.44 (5.46) .67 .61 −0.08 Barthel −3.30 (8.09) .29 −0.11 (3.98) .92 .74 −0.50 MRCp −0.12 (0.78) >.99 0.28 (0.46) .06 .06 −0.62 MRCd 0.29 (0.77) .25 0.17 (0.62) 45 .98 −0.17 Asp 0.06 (0.65) >.99 0.00 (0.34) >.99 >.99 −0.12 0.29 (0.59) .13 0.00 (0.00) >.99 .03 0.70 Asd Grip force 0.21 (1.45) .73 0.23 (3.02) .92 .93 −0.01 Hamilton 0.35 (2.34) .70 1.11 (3.53) .42 .93 −0.25 VAS-S 0.12 (2.06) .92 0.78 (3.08) .38 .27 −0.25 UE-FM: The upper extremity Fugl-Meyer Assessment. CAHAI: Chedoke Arm and Hand Activity Inventory (version CAHAI-13). MRCp: Medical Research Council for proximal muscles. MRCd: Medical Research Council for distal muscles. Asp: Ashworth Scale for proximal muscles. Asd: Ashworth Scale for distal muscles. VAS-S: Visual Analog Scale for Shoulder Pain. hemispheres along the mediolateral, and the anteroposterior RGS Induced Changes in the Corticospinal System axis (P<.05, Wilcoxon). In the non-pathological hemisphere, In order to detect training-induced changes in the corticospinal the cortical substrate representing the ECR was significantly system, we first characterized cortical regions in the primary larger than the area corresponding to the APB muscle (P<.05, motor area of the pathological and non-pathological hemispheres Wilcoxon). Interestingly, this difference was not present in the representing abductor pollicis brevis (APB) and extensor-carpi pathological hemisphere. radialis (ECR) muscles. At baseline, the Stimulation Efficacy SE increased significantly within subject after treatment in the (SE) was significantly higher for the non-pathological pathological hemisphere (3.6, SD 8.60; P<.01, Wilcoxon). This hemisphere when compared to the pathological one (P<.01, change was significant only for the RGS group (4.17, SD 9.86; Wilcoxon) (Figure 4). We observed that the centroid of the cortical area that produced MEPs was different between http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 7 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al P<.01, Wilcoxon; d=.6) and the APB muscle (5.21, SD 10.98; CAHAI (r =.92, P<.01), and Barthel (r =.68, P<.05), while the s s P=.05, Wilcoxon; d=.66) [29]. same effect was not present in the ECR muscle (r <.61, P>.14). In addition, centroid displacements measured after intervention We observed a centroid displacement in the pathological for the APB muscle were strongly correlated with UE-FM hemisphere, which occurred after treatment both for the APB (r =.87, P<.05), CAHAI (r =.99, P<.01), and Barthel (r =.81, s s s and the ECR muscle (Figure 4). Since changes in cortical P<.05). Centroid displacements for the ECR muscle also showed organization may indicate actual motor gains, we correlated strong correlations with UE-FM (r =.99, P<.01), and CAHAI post-treatment changes in SEs and centroid displacements with improvements at week 3 that were captured by the clinical scales (r =.89, P<.05) clinical scales. Changes in the area of the cortical [30]. Changes in SEs for the APB muscle strongly correlated regions associated with each of the two muscles did not show with improvements in UE-FM (r =.86, P<.01) (Figure 4), s any significant correlation with the improvements in clinical scales. Figure 4. Effects of domiciliary rehabilitation therapy on corticospinal efficacy. (A) Change in mean Stimulation Efficacy for extensor-carpi radialis (ECR) in the damaged hemisphere (pathological) and the intact hemisphere (non-pathological). (B) Change in mean Stimulation Efficacy for abductor pollicis brevis (APB). (C) Centroid displacements after therapy along anterioposterior and mediolateral axis. (D) Correlation of absolute centroid displacements after therapy with improvement in CAHAI score after therapy. First, we validated the RGS Adaptive Difficulty Controller, Discussion which automatically provides for a limb specific customization of practice difficulty and intensity, and a progress-monitoring Principal Findings tool. We observed lower success rates during the execution of We have studied the effectiveness of the RGS VR-based system those subtasks involving distal movements (ie, Grasp and Place). for home-based motor rehabilitation of the upper extremities Lateralized customization of task difficulty allowed for the after stroke by conducting a controlled, longitudinal clinical maintenance of optimal performance levels for each limb across trial assessing both functional and structural impact and sessions. Within-subject analysis of the evolution of the comparing it to an OT task. We have shown that, at the chronic difficulty parameters assigned during training revealed paretic stage post-stroke, the remote delivery of customized limb specific functional improvements during a reaching and self-managed motor training in VR environments may grasping task. These observations may indicate functional gains effectively induce motor gains and neuroplastic changes. of distal function (ie, increased control in fingers flexion and Comparisons between groups suggest a superiority of VR extension). Data collected by the Automated Evaluation of compared with OT in domiciliary setups, however, this Motor Function further confirmed these findings, revealing difference does not reach clinical impact. Our results highlight significant improvements for the paretic limb, during week 2 the potential of automated rehabilitation technologies for and 3, in finger flexion. Interestingly, we also found an domiciliary neurorehabilitation, which so far has been an issue improvement in range of movement both for the paretic and of some contention [31]. non-paretic limb, probably indicating a generalization of new http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 8 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al cognitive and compensatory strategies. Notice that subjects organization, the severity of hemiparesis is often greatest in the included in this study were in the chronic phase of stroke (mean distal muscles and least in the proximal muscles of the upper time post stroke 65.05 months, SD 10.3), a period in which extremity [42]. Interestingly, this disparity may only appear at motor improvements are supposed to have plateaued and limited the chronic stage [18]. Consistent with these observations, non-compensatory functional gains can still be induced through participants showed a greater muscle weakness at baseline for further physical or OT [32]. We show that the RGS group distal than for proximal muscle groups (Table 1), which may displayed significant gains on the CAHAI scale as compared be associated with a distal to proximal recovery process at this to control. However, these changes did not reach the minimal later stage post-stroke [43]. The specific factors involved in detectable change (MDC=6.3 points) and we observed no causing the observed RGS-derived improvements in distal retention of the improvements at follow-up, suggesting that function as compared to OT are not fully explained by our achievement and retention of clinically relevant improvements results. For instance, training in these two conditions differed at the chronic stage post-stroke may depend on longer in some aspects. On the one hand, RGS explicitly prevented the intervention periods [30]. We did not observe any significant execution of compensatory body movements by capturing only changes in the UE-FM scale, in any of the groups, perhaps due joint flexion and extension and filtering out the participant’s to the lack of responsiveness of this scale at the chronic stage trunk movements [44]. In contrast, participants in the control post-stroke [33]. An alternative explanation for the lack of effect group, who followed a domiciliary OT protocol, without any in the UE-FM scale is that these improvements may be supervision, may not have reached sufficient training intensity fundamentally related to compensatory changes at the Body or may have reinforced the execution of functional Functions and Structure and Activity levels [34]. compensatory movements (eg, overusing the non-paretic limb or performing trunk displacements) [45]. On the other hand, Results from the NBS protocol supported these findings by participants assigned to the RGS group repeatedly performed displaying an enhanced corticospinal excitability after treatment goal-oriented visuomotor transformations in order to control only for the more distal muscle (ABP) associated with hand the virtual analogue of their paretic and non-paretic limbs, which function. In addition, we observed centroid displacements of may induce increased neural activity in cortical motor areas the cortical map for both the ABP and the ECR. This confirms [40,46]. Indeed, we have shown that in healthy controls exposure earlier reports that enhanced corticospinal excitability and to the RGS scenario leads to significantly enhance activity in cortical map centroid displacements strongly correlate with premotor areas [47]. The OT group, however, was not exposed functional gains detected by standardized clinical scales, such to such transformations, indeed subjects in this group performed as Fugl-Meyer, CAHAI, and Barthel scales [30,32,35-37]. repetitive visuomotor tasks in the real world only, where visual Previous research suggests that an imaging measure of exposure to motor movements performed with the paretic limb corticospinal tract (CST) injury in the acute phase can predict may not be critical for successful performance. Although these motor outcome at 3 months [38]. Our results show that are factors that could be better controlled in OT, our objective NBS-derived measures of corticospinal connectivity may be was to achieve a fair comparison between RGS virtual reality also relevant biomarkers for identifying chronic stroke survivors based and standard domiciliary OT and to understand their who have the potential to respond to a particular rehabilitative relative impact. In addition to motor gains, we observed a therapy and may be predictive of patient prognosis. Overall, reduction in shoulder pain in the VR group, captured by the these plastic changes may be use-dependent; an increase in the VAS scale. The reason for this effect may be that the VR group use of the paretic limb during the intervention period may have did not have to perform repetitive movements at the shoulder unmasked preexisting excitatory connections or even enhanced joint, unlike the control group. This difference could also explain the efficacy of existing neuronal networks. Thus, RGS-induced the trend in an increase in muscle strength for the proximal cortical changes could be related to a greater activation in the musculature in the control group. ipsilesional hemisphere, as has been proposed by previous studies [39,40]. Conclusions In this randomized controlled study, we explored the effects of Limitations a VR-based system for domiciliary rehabilitation on functional Taking a global perspective on these results, we observe that recovery and cortical reorganization. Our results suggest that task difficulty descriptors, AEMF measurements, and NBS, at-home VR-based rehabilitation promotes functional motor converged, suggesting that distal functional improvements were gains, enhances corticospinal excitability, and induces cortical induced through RGS based training and were significantly reorganization at the chronic stage post- stroke. The observation larger for those participants in the RGS group when compared of strong correlations between increased motor evoked potentials with the control group. The reason why we may not have after treatment and functional gains in CAHAI suggests that observed improvements in proximal muscle groups and other exposure to VR-based goal-oriented motor training may have clinical scales may be related to the stringent inclusion criteria enhanced the organization of corticospinal pathways, facilitating of the study, which excluded all subjects showing severe distal motor control. The displacement of the centroid of cortical hemiparesis at baseline (Proximal Medical Research Council, maps after training may also indicate related cortical MRC>2). It is widely known that the corticospinal system is reorganization at the chronic stage post-stroke supporting the organized following a proximal to distal gradient to the cervical idea that recovery can be induced at any stage post stroke albeit spinal cord, where motoneurons of the distal muscle groups to varying degrees. receive most input projections [41]. Due to this hierarchical http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 9 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al Acknowledgments We would like to thank all subjects who participated in this study. We also would like to gratefully acknowledge Estefanía Montiel for her assistance in recruiting and evaluating the participants. This work was supported by the MINECO “Retos Investigacion tos Investigacion I + D + I” Plan Nacional project SANAR (Gobierno de España), and the European Research Council under grant agreement 341196 CDAC and FP7-ICT- 270212 project eSMC. Conflicts of Interest PV is involved in the spin-off company Eodyne Systems SL, which has the goal to achieve a large-scale distribution of science based rehabilitation technologies. Multimedia Appendix 1 CONSORT eHealth form. [PDF File (Adobe PDF File), 66KB-Multimedia Appendix 1] References 1. Shah S, Vanclay F, Cooper B. Predicting discharge status at commencement of stroke rehabilitation. Stroke 1989 Jun 01;20(6):766-769. [doi: 10.1161/01.STR.20.6.766] 2. Lai S, Studenski S, Duncan P, Perera S. Persisting consequences of stroke measured by the Stroke Impact Scale. Stroke 2002 Jul;33(7):1840-1844 [FREE Full text] [Medline: 12105363] 3. Shaughnessy M, Resnick B, Macko R. Testing a model of post-stroke exercise behavior. Rehabil Nurs 2006;31(1):15-21. [Medline: 16422040] 4. Hopman W, Verner J. Quality of life during and after inpatient stroke rehabilitation. Stroke 2003 Feb 13;34(3):801-805 [FREE Full text] [doi: 10.1161/01.STR.0000057978.15397.6F] 5. Anderson C, Mhurchu C, Rubenach S, Clark M, Spencer C, Winsor A. Home or hospital for stroke Rehabilitation? results of a randomized controlled trial : II: cost minimization analysis at 6 months. Stroke 2000 May;31(5):1032-1037 [FREE Full text] [Medline: 10797162] 6. Widén HL, von KL, Kostulas V, Holm M, Widsell G, Tegler H, et al. A randomized controlled trial of rehabilitation at home after stroke in southwest Stockholm. Stroke 1998 Mar;29(3):591-597 [FREE Full text] [Medline: 9506598] 7. Simpson L, Eng J, Chan M. H-GRASP: the feasibility of an upper limb home exercise program monitored by phone for individuals post stroke. Disabil Rehabil 2017 May;39(9):874-882 [FREE Full text] [doi: 10.3109/09638288.2016.1162853] [Medline: 27017890] 8. Mayo N, Wood-Dauphinee S, Côté R, Gayton D, Carlton J, Buttery J, et al. There's no place like home : an evaluation of early supported discharge for stroke. Stroke 2000 May;31(5):1016-1023 [FREE Full text] [Medline: 10797160] 9. Garrido NJ, Ruiz PV, Lozano PM. Movement-based interaction applied to physical rehabilitation therapies. J Med Internet Res 2014 Dec 09;16(12):e281 [FREE Full text] [doi: 10.2196/jmir.3154] [Medline: 25491148] 10. Hillier S, Inglis-Jassiem G. Rehabilitation for community-dwelling people with stroke: home or centre based? a systematic review. Int J Stroke 2010 Jun;5(3):178-186. [doi: 10.1111/j.1747-4949.2010.00427.x] [Medline: 20536615] 11. Rose F, Brooks B, Rizzo A. Virtual reality in brain damage rehabilitation: review. Cyberpsychol Behav 2005 Jun;8(3):241-62; discussion 263. [doi: 10.1089/cpb.2005.8.241] [Medline: 15971974] 12. Lewis G, Rosie J. Virtual reality games for movement rehabilitation in neurological conditions: how do we meet the needs and expectations of the users? Disabil Rehabil 2012;34(22):1880-1886. [doi: 10.3109/09638288.2012.670036] [Medline: 22480353] 13. Cameirão MS, Badia SB, Duarte E, Frisoli A, Verschure PF. The combined impact of virtual reality neurorehabilitation and its interfaces on upper extremity functional recovery in patients with chronic stroke. Stroke 2012 Oct;43(10):2720-2728 [FREE Full text] [doi: 10.1161/STROKEAHA.112.653196] [Medline: 22871683] 14. McEwen D, Taillon-Hobson A, Bilodeau M, Sveistrup H, Finestone H. Virtual reality exercise improves mobility after stroke: an inpatient randomized controlled trial. Stroke 2014 Jun;45(6):1853-1855 [FREE Full text] [doi: 10.1161/STROKEAHA.114.005362] [Medline: 24763929] 15. Rizzo A. Virtual reality and disability: emergence and challenge.  Disabil Rehabil 2009 Jul 07;24(11-12):567-569 [FREE Full text] [doi: 10.1080/09638280110111315] 16. Cameirão MS, Badia SB, Oller ED, Verschure PF. Neurorehabilitation using the virtual reality based rehabilitation gaming system: methodology, design, psychometrics, usability and validation. J Neuroeng Rehabil 2010 Sep 22;7:48 [FREE Full text] [doi: 10.1186/1743-0003-7-48] [Medline: 20860808] 17. Dickstein R, Deutsch J. Motor imagery in physical therapist practice. Phys Ther 2007 Jul;87(7):942-953. [doi: 10.2522/ptj.20060331] [Medline: 17472948] 18. Lang CE, Wagner JM, Bastian AJ, Hu Q, Edwards DF, Sahrmann SA, et al. Deficits in grasp versus reach during acute hemiparesis. Exp Brain Res 2005 Sep;166(1):126-136. [doi: 10.1007/s00221-005-2350-6] [Medline: 16021431] http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 10 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al 19. Nirme J, Duff A, Verschure PF. Adaptive rehabilitation gaming system: on-line individualization of stroke rehabilitation. Conf Proc IEEE Eng Med Biol Soc 2011;2011:6749-6752. [doi: 10.1109/IEMBS.2011.6091665] [Medline: 22255888] 20. Csikszentmihalyi M. Flow: the classic work on how to achieve happiness. London: Rider; 2002. 21. Gladstone D, Danells C, Black S. The fugl-meyer assessment of motor recovery after stroke: a critical review of its measurement properties. Neurorehabil Neural Repair 2002 Sep;16(3):232-240. [doi: 10.1177/154596802401105171] [Medline: 12234086] 22. Barreca S, Stratford P, Lambert C, Masters L, Streiner D. Test-retest reliability, validity, and sensitivity of the Chedoke arm and hand activity inventory: a new measure of upper-limb function for survivors of stroke. Arch Phys Med Rehabil 2005 Aug;86(8):1616-1622. [doi: 10.1016/j.apmr.2005.03.017] [Medline: 16084816] 23. Collin C, Wade D, Davies S, Horne V. The Barthel ADL Index: a reliability study. Int Disabil Stud 1988;10(2):61-63. [Medline: 3403500] 24. Bohannon RW, Smith MB. Interrater reliability of a modified Ashworth scale of muscle spasticity. Phys Ther 1987 Feb;67(2):206-207. [Medline: 3809245] 25. Wadsworth CT, Krishnan R, Sear M, Harrold J, Nielsen DH. Intrarater reliability of manual muscle testing and hand-held dynametric muscle testing. Phys Ther 1987 Sep;67(9):1342-1347. [Medline: 3628487] 26. Knesevich JW, Biggs JT, Clayton PJ, Ziegler VE. Validity of the Hamilton rating Scale for depression. Br J Psychiatry 1977 Jul;131:49-52. [Medline: 884416] 27. Bijur P, Silver W, Gallagher E. Reliability of the visual analog scale for measurement of acute pain. Acad Emerg Med 2001 Dec;8(12):1153-1157 [FREE Full text] [Medline: 11733293] 28. Ruohonen J, Karhu J. Navigated transcranial magnetic stimulation. Neurophysiol Clin 2010 Mar;40(1):7-17. [doi: 10.1016/j.neucli.2010.01.006] [Medline: 20230931] 29. Dunlap W, Cortina JM, Vaslow J, Burke M. Meta-analysis of experiments with matched groups or repeated measures designs.  Psychol Methods 1996;1(2):170-177. [doi: 10.1037/1082-989X.1.2.170] 30. Liepert J, Miltner W, Bauder H, Sommer M, Dettmers C, Taub E, et al. Motor cortex plasticity during constraint-induced movement therapy in stroke patients. Neurosci Lett 1998 Jun 26;250(1):5-8. [Medline: 9696052] 31. Coupar F, Pollock A, Legg LA, Sackley C, van Vliet P. Home-based therapy programmes for upper limb functional recovery following stroke. Cochrane Database Syst Rev 2012 May 16(5):CD006755. [doi: 10.1002/14651858.CD006755.pub2] [Medline: 22592715] 32. Murphy T, Corbett D. Plasticity during stroke recovery: from synapse to behaviour. Nat Rev Neurosci 2009 Dec;10(12):861-872. [doi: 10.1038/nrn2735] [Medline: 19888284] 33. Nudo R, Milliken G, Jenkins W, Merzenich M. Use-dependent alterations of movement representations in primary motor cortex of adult squirrel monkeys. J Neurosci 1996 Jan 15;16(2):785-807 [FREE Full text] [Medline: 8551360] 34. Levin MF, Kleim JA, Wolf SL. What do motor recovery and compensation mean in patients following stroke? Neurorehabil Neural Repair 2009 May;23(4):313-319. [doi: 10.1177/1545968308328727] [Medline: 19118128] 35. Zhu LL, Lindenberg R, Alexander MP, Schlaug G. Lesion load of the corticospinal tract predicts motor impairment in chronic stroke. Stroke 2010 May;41(5):910-915 [FREE Full text] [doi: 10.1161/STROKEAHA.109.577023] [Medline: 20378864] 36. Thickbroom GW, Byrnes ML, Archer SA, Mastaglia FL. Motor outcome after subcortical stroke correlates with the degree of cortical reorganization. Clin Neurophysiol 2004 Sep;115(9):2144-2150. [doi: 10.1016/j.clinph.2004.04.001] [Medline: 15294217] 37. Kim Y, You SH, Ko M, Park J, Lee KH, Jang SH, et al. Repetitive transcranial magnetic stimulation-induced corticomotor excitability and associated motor skill acquisition in chronic stroke. Stroke 2006 Jun;37(6):1471-1476 [FREE Full text] [doi: 10.1161/01.STR.0000221233.55497.51] [Medline: 16675743] 38. Yu X, Song R, Jiaerken Y, Yuan L, Huang P, Lou M, et al. White matter injury induced by diabetes in acute stroke is clinically relevant: a preliminary study. Diab Vasc Dis Res 2017 Jan;14(1):40-46. [doi: 10.1177/1479164116675491] [Medline: 27941055] 39. Sung H, You S, Hallett M, Yun W, Park C, Cho S. Cortical reorganization and associated functional motor recovery after virtual reality in patients with chronic stroke: An experimenter-blind preliminary study. Arch Phys Med Rehabil 2005;86(11):2218-2223. [Medline: 16271575] 40. Saleh S, Adamovich SV, Tunik E. Mirrored feedback in chronic stroke: recruitment and effective connectivity of ipsilesional sensorimotor networks. Neurorehabil Neural Repair 2014 May;28(4):344-354 [FREE Full text] [doi: 10.1177/1545968313513074] [Medline: 24370569] 41. Clough J, Kernell D, Phillips C. The distribution of monosynaptic excitation from the pyramidal tract and from primary spindle afferents to motoneurones of the baboon's hand and forearm. J Physiol 1968 Sep;198(1):145-166 [FREE Full text] [Medline: 16992310] 42. Colebatch J, Gandevia S. The distribution of muscular weakness in upper motor neuron lesions affecting the arm. Brain 1989 Jun;112 (Pt 3):749-763. [Medline: 2731028] http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 11 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al 43. Lambercy O, Dovat L, Yun H, Wee SW, Kuah CW, Chua KS, et al. Effects of a robot-assisted training of grasp and pronation/supination in chronic stroke: a pilot study. J Neuroeng Rehabil 2011 Nov 16;8:63 [FREE Full text] [doi: 10.1186/1743-0003-8-63] [Medline: 22087842] 44. Cameirão MS, Badia SB, Duarte E, Frisoli A, Verschure PF. The combined impact of virtual reality neurorehabilitation and its interfaces on upper extremity functional recovery in patients with chronic stroke. Stroke 2012 Oct;43(10):2720-2728 [FREE Full text] [doi: 10.1161/STROKEAHA.112.653196] [Medline: 22871683] 45. Michaelsen S, Dannenbaum R, Levin M. Task-specific training with trunk restraint on arm recovery in stroke: randomized control trial. Stroke 2006 Jan;37(1):186-192 [FREE Full text] [doi: 10.1161/01.STR.0000196940.20446.c9] [Medline: 16339469] 46. Tunik E, Saleh S, Bagce H, Merians A, Adamovich SV. Mirror feedback in virtual reality elicits ipsilesional motor cortex activation in chronic stroke patients. 2011 Jun 27 Presented at: Int Conf Virtual Rehabilitation ICVR; 2011; Zurich URL: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5971862 [doi: 10.1109/ICVR.2011.5971862] 47. Seitz R, Huang Y, Knorr U, Tellmann L, Herzog H, Freund HJ. Large-scale plasticity of the human motor cortex. Neuroreport 1995 Mar 27;6(5):742-744. [Medline: 7605938] Abbreviations AEMF: automated evaluation of motor function APB: abductor pollicis brevis ASd: Ashworth scale for distal upper limb ASp: Ashworth scale for proximal upper limb BI: barthel index CAHAI: chedoke arm and hand activity inventory ECR: extensor-carpi radialis MMSE: mini-mental state evaluation MRC: medical research council scale NBS: navigated brain stimulation OT: occupational therapy RGS: rehabilitation gaming system SE: simulation efficacy UE-FM: the upper extremity Fugl-Meyer assessment VAS: visual analog scale VR: virtual reality Edited by G Eysenbach; submitted 09.10.16; peer-reviewed by I Cikajlo, R Lloréns, D Putrino; comments to author 09.01.17; revised version received 04.04.17; accepted 29.04.17; published 07.08.17 Please cite as: Ballester BR, Nirme J, Camacho I, Duarte E, Rodríguez S, Cuxart A, Duff A, Verschure PF Domiciliary VR-Based Therapy for Functional Recovery and Cortical Reorganization: Randomized Controlled Trial in Participants at the Chronic Stage Post Stroke JMIR Serious Games 2017;5(3):e15 URL: http://games.jmir.org/2017/3/e15/ doi: 10.2196/games.6773 PMID: 28784593 ©Belén Rubio Ballester, Jens Nirme, Irene Camacho, Esther Duarte, Susana Rodríguez, Ampar Cuxart, Armin Duff, Paul F.M.J. Verschure. Originally published in JMIR Serious Games (http://games.jmir.org), 07.08.2017. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Serious Games, is properly cited. The complete bibliographic information, a link to the original publication on http://games.jmir.org, as well as this copyright and license information must be included. http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 12 (page number not for citation purposes) XSL FO RenderX http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JMIR Serious Games JMIR Publications

Domiciliary VR-Based Therapy for Functional Recovery and Cortical Reorganization: Randomized Controlled Trial in Participants at the Chronic Stage Post Stroke

Loading next page...
 
/lp/jmir-publications/domiciliary-vr-based-therapy-for-functional-recovery-and-cortical-99nd6NI4FB

References (50)

Publisher
JMIR Publications
Copyright
Copyright © The Author(s). Licensed under Creative Commons Attribution cc-by 4.0
ISSN
2291-9279
DOI
10.2196/games.6773
Publisher site
See Article on Publisher Site

Abstract

Background: Most stroke survivors continue to experience motor impairments even after hospital discharge. Virtual reality-based techniques have shown potential for rehabilitative training of these motor impairments. Here we assess the impact of at-home VR-based motor training on functional motor recovery, corticospinal excitability and cortical reorganization. Objective: The aim of this study was to identify the effects of home-based VR-based motor rehabilitation on (1) cortical reorganization, (2) corticospinal tract, and (3) functional recovery after stroke in comparison to home-based occupational therapy. Methods: We conducted a parallel-group, controlled trial to compare the effectiveness of domiciliary VR-based therapy with occupational therapy in inducing motor recovery of the upper extremities. A total of 35 participants with chronic stroke underwent 3 weeks of home-based treatment. A group of subjects was trained using a VR-based system for motor rehabilitation, while the control group followed a conventional therapy. Motor function was evaluated at baseline, after the intervention, and at 12-weeks follow-up. In a subgroup of subjects, we used Navigated Brain Stimulation (NBS) procedures to measure the effect of the interventions on corticospinal excitability and cortical reorganization. Results: Results from the system’s recordings and clinical evaluation showed significantly greater functional recovery for the experimental group when compared with the control group (1.53, SD 2.4 in Chedoke Arm and Hand Activity Inventory). However, functional improvements did not reach clinical significance. After the therapy, physiological measures obtained from a subgroup of subjects revealed an increased corticospinal excitability for distal muscles driven by the pathological hemisphere, that is, abductor pollicis brevis. We also observed a displacement of the centroid of the cortical map for each tested muscle in the damaged hemisphere, which strongly correlated with improvements in clinical scales. Conclusions: These findings suggest that, in chronic stages, remote delivery of customized VR-based motor training promotes functional gains that are accompanied by neuroplastic changes. Trial Registration: International Standard Randomized Controlled Trial Number NCT02699398 (Archived by ClinicalTrials.gov at https://clinicaltrials.gov/ct2/show/NCT02699398?term=NCT02699398&rank=1) (JMIR Serious Games 2017;5(3):e15) doi: 10.2196/games.6773 http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 1 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al KEYWORDS stroke; movement disorder; recovery of function, neuroplasticity; transcranial magnetic stimulation; physical therapy; hemiparesis; computer applications software Participants Introduction Participants were first approached by an occupational therapist After initial hospitalization, many stroke patients return home from the rehabilitation units of Hospital Esperanza and Hospital relatively soon despite still suffering from impairments that Vall d’Hebron from Barcelona to determine their interest in require continuous rehabilitation [1]. Therefore, ¼ to ¾ of participating in a research project. Recruited participants met patients display persistent functional limitations for a period of the following inclusion criteria: (1) mild-to-moderate 3 to 6 months after stroke [2]. Although clinicians may prescribe upper-limbs hemiparesis (Proximal MRC>2) secondary to a a home exercise regimen, reports indicate that only one-third first-ever stroke (>12 months post-stroke), (2) age between 45 of patients actually accomplish it [3]. Consequently, substantial and 85 years old, (3) absence of any major cognitive impairment gains in health-related quality of life during inpatient stroke (Mini-Mental State Evaluation, MMSE>22), and (4) previous rehabilitation may be followed by equally substantial declines experience with RGS in the clinic. The ethics committee of in the 6 months after discharge [4]. Multiple studies have shown, clinical research of the Parc de Salut Mar and Vall d’Hebron however, that supported discharge combined with at home Research Institute approved the experimental guidelines. rehabilitation services does not compromise clinical inpatient Thirty-nine participants at the chronic stage post-stroke were outcomes [5-7] and may enhance recovery in subacute stroke recruited for the study by two occupational therapists, between patients [8]. Hence, it is essential that new approaches are October 2011 and January 2012, and were assigned to a RGS deployed that help to manage chronic conditions associated (n=20) or a control group (n=19) using stratified permuted block with stroke, including domiciliary interventions [9] and the randomization methods for balancing the participants’ augmentation of current rehabilitation approaches in order to demographics and clinical scores at baseline (Table 1). One enhance their efficiency. There should be increased provision participant in the RGS group refused to participate. Prior to the of home-based rehabilitation services for community-based experiment, participants signed informed consent forms. This adults following strok e, taking cost-effectiveness, and a quick trial was not registered at or before the onset of participants’ family and social reintegration into account [10]. enrollment because it is a pilot study that evaluates the feasibility of a prototype device. However, this study was registered One of the latest approaches in rehabilitation science is based retrospectively in ClinicalTrials.gov and has the identifier on the use of robotics and virtual reality (VR), which allow NCT02699398. remote delivery of customized treatment by combining dedicated interface devices with automatized training scenarios [10-12]. Instrumentation Several studies have tested the acceptability of VR-based setups Description of the Rehabilitation Gaming System as an intervention and evaluation tool for rehabilitation [13-15]. The RGS integrates a paradigm of goal-directed action execution One example of this technology is the, so called, Rehabilitation and motor imagery [17], allowing the user to control a virtual Gaming System (RGS) [16], which has been shown to be body (avatar) through an image capture device (Figure 1). For effective in the rehabilitation of the upper extremities in the this study, we developed training and evaluation scenarios within acute and the chronic phases of stroke [13]. However, so far the RGS framework. In the Spheroids training scenario (Figure little work exists on the quantitative assessment of the clinical 1), the user has to perform bilateral reaching movements to impact of VR based approaches and their effects on neural intercept and grasp a maximum number of spheres moving reorganization that can directly inform the design of these towards him [16]. RGS captures only joint flexion and extension systems and their application in the domiciliary context. The and filters out the participant’s trunk movements, therefore main objective of this paper is to further explore the potential preventing the execution of compensatory body movements and limitations of VR technologies in domiciliary settings. [18]. This task was defined by three difficulty parameters, each Specifically, we examine the efficacy of a VR-based therapy of them associated with a specific performance descriptor: (1) when used at home for (1) assessing functional improvement, different trajectories of the spheres require different ranges of (2) facilitating functional recovery of the upper-limbs, and (3) joint motion for elbow and shoulder, (2) the size of the spheres inducing cortical reorganization. This is the first study testing require different hand and grasp precision and perceptual the effects of VR-based therapy on cortical reorganization and abilities, and (3) the velocity of the spheres require different corticospinal integrity using NBS. movement speeds and timing. All these parameters, also including the range of finger flexion and extension required to Methods grasp and release spheroids, were dynamically modulated by Design the RGS Adaptive Difficulty Controller [19] to maintain the performance ratio (ie, successful trials over the total trials) above We conducted a parallel-group, controlled trial in order to 0.6 and below 0.8, optimizing effort and reinforcement during compare the effectiveness of domiciliary VR-based therapy training [20]. versus domiciliary occupational therapy (OT) in inducing functional recovery and cortical reorganization in chronic stroke patients. http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 2 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al Figure 1. Experimental setup and protocol: (A) Movements of the user’s upper limbs are captured and mapped onto an avatar displayed on a screen in first person perspective so that the user sees the movements of the virtual upper extremities. A pair of data gloves equipped with bend sensors captures finger flexion. (B) The Spheroids is divided into three subtasks: hit, grasp, and place. A white separator line divides the workspace in a paretic and non-paretic zone only allowing for ipsilateral movements.(C) The experimental protocol. Evaluation periods (Eval.) indicate clinical evaluations using standard clinical scales and Navigated Brain Stimulation procedures (NBS). These evaluations took place before the first session (W0), after the last session of the treatment (day 15, W3), and at follow-up (week 12, W12). rehabilitation during 5 weekly days, for 3 consecutive weeks. Description of the Evaluation Scenario The RGS group followed a home-based training paradigm based Designing automated evaluation tools to be used at-home in a on the Spheroids scenario (Figure 1), comprising 3 consecutive non-supervised setup could provide objective and frequent subtasks: Hit, Grasp, and Place, with a total duration of 20 measurements of recovery, offering valuable information to minutes, 6 minutes, and 40 seconds each. Participants in the clinicians and primary users, and driving autonomous RGS group completed the Automated Evaluation of Motor rehabilitation technologies. We, therefore, developed the Function once a day, before the training session, which lasted Automated Evaluation of Motor Function (AEMF), a VR-based 2 minutes and 30 seconds. We delivered the system and trained evaluation scenario for the assessment of upper-limb motor the participants and their corresponding caregivers to use the function that was designed to operate under non-supervised system without supervision. The control group performed a 20 conditions. minutes OT task at home, without assistance, which consisted of horizontal and vertical stacking and unstacking of plastic Description of the Automated Evaluation of Motor cups with their right and left hand consecutively. This task was Function (AEMF) designed by an occupational therapist to match the movements In order to assess proximal and distal motor function, the AEMF trained during the RGS task. At the end of the therapy, the scenario is divided into two separated tasks. In task 1, participants reported to have completed a minimum of 1 session participants were asked to perform planar wiping movements a day. In the RGS group, the therapy time was similarly split with their arms to clear a virtual surface covered with small between 10 minutes of activity with the affected hand and 10 cubes. In task 2, participants were instructed to squeeze a virtual minutes with the less affected hand. All participants were asked object by flexing and extending their fingers. In order to to perform a minimum of 1 and a maximum of 3 training guarantee that the AEMF tasks were correctly understood, each sessions a day. of these was first performed using the non-paretic limb and then Outcome Measures with the paretic limb. Participants did not receive any explicit feedback (ie, knowledge of results) about their overall All participants’ motor function was evaluated at day 1, day 15 performance. During task execution, we collected data of hand of the rehabilitation program, and week 12 follow-up (Figure position and joint rotation (fingers, elbows, and shoulders) to 1), using 8 standard clinical scales. Evaluations were carried compute three main performance descriptors: the horizontal out by two occupational therapists who were not blinded to planar area covered, finger flexion, and extension. treatment assignment. Primary outcomes were the improvement in the upper extremity section of the Fugl-Meyer Assessment Experimental Protocol (UE-FM) [21], and the Chedoke Arm and Hand Activity In order to test the effectiveness of VR in the domiciliary Inventory (CAHAI) [22]. Secondary outcomes were context, each participant received daily home-based upper-limb improvements in Barthel Index (BI) [23], Ashworth Scale for http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 3 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al distal (ASd) and proximal upper limb (ASp) [24], Medical synchronized with a three-dimensional tracking system Research Council Scale for distal (MRCd) and proximal upper (Navigated Brain System, Nexstim, Eximia, Finland). Motor limb (MRCp) [25], and grip force. In addition, we used the evoked potentials (MEPs) were recorded using surface Hamilton Scale to assess mood disorders [26], and the Visual electrodes (Ambu, Neuroline 700), connected to a 4 channel Analog Scale (VAS) to evaluate shoulder pain [27]. electromyographic (EMG) system (Key-Point net, Medtronic, USA). Data collected during NBS was analyzed to estimate the Both during the training and evaluation sessions, we captured motor threshold at rest (RMT) for abductor pollicis brevis (APB) the user’s movements and mapped them onto a biomechanical and extensor-carpi radialis (ECR) for each participant. The RMT model of the upper limbs. Specifically, virtual movements were was defined as the intensity of TMS stimulus needed to obtain controlled by the angles of the users’ joints measured by a more than 50% of responses with amplitudes over 50 μV. After motion capture device at 30Hz (Kinect, Microsoft, USA). The finding the RMT of both muscles we proceeded to draw the range of finger flexion was captured by a pair of data gloves cortical maps of both the healthy and pathological hemisphere (DGTech Engineering Solutions, Bazzano, Italy) equipped with in each participant. Maps were drawn at 110% of RMT, a bend sensors, measures range from 0 to 1, indicating maximum percentage commonly used to avoid no-response spots and extension and maximum flexion respectively. suppressive effects. When no-response was found on the Navigated Brain Stimulation (NBS) procedures [28] were used pathological side we incremented the stimulus intensity stepwise to assess training-induced changes in the functional integrity in a logarithmic fashion (ie, 110%, 120%, and 140%) until the of the pyramidal tract and cortical maps in the primary motor maximum stimulator output was reached. To determine the area (M1). A total of 17 participants (3 of them assigned to the boundaries, we stopped searching a particular direction until control group) accepted to participate in the NBS procedure, two no-response points aligned in the same vector and direction which was conducted for each subject before and after treatment or when the sulcus boundaries were reached. After processing (Figure 2). A 3-Tesla magnet (Philips Achieva) was used for the data, we characterized cortical representations of APB and 3D MRI acquisitions. In order to faithfully build a 3D model ECR and corticospinal connectivity in each cerebral hemisphere of the participant’s scalp and parenchyma we used T1W- by estimating the centroid of the cortical motor output map and 3D-TFE acquired sequences comprising a minimum of 178 their corresponding Stimulation Efficacy (SE). SE was the slices. For nTMS mapping we used a butterfly coil (MC-B70, greatest value in the 80th percentile of the MEPs divided by the Medtronic, Alpine, USA), and magnetic stimulation equipment maximum stimulation intensity. (Mag Pro-30 with MagOption, Medtronic, Alpine, USA) Figure 2. Navigated Brain Stimulation (NBS) procedure. Bottom right: axial and coronal view of a magnetic resonance imaging (MRI) scan at the level of the stroke for one of the participants in the experimental group showing a partial anterior circulation infarct due to an embolism. Bottom right: Example of NBS mapped cortical motor representations; colored areas indicate the targeted cortical sites. In order to validate the RGS Adaptive Difficulty Controller, Data Analysis automatic performance ratios and difficulty parameters assigned For statistical analysis, data were tested for normality using the by RGS to the paretic and non-paretic limb were compared Kolmogorov-Smirnov test. To identify significant time effects (Wilcoxon signed-rank test). Next, to explicitly study progress on clinical scores we performed a Friedman test. Next, we in performance, we averaged values for each difficulty parameter conducted a post-hoc analysis using 2-tailed Mann-Whitney U per session and performed a within-subjects time-series analysis tests to compare improvements between groups at week 3 and of the means (Friedman test). week 12 follow-up. Within-subject analysis of recovery was Data of hand position and joint rotation collected during assessed using standard clinical scales (Table 1). We reversed performance in AEMF were filtered using a second order the polarity of Hamilton, VAS and Ashworth scales so that Butter-worth low- pass filter (cut-off at 6 Hz) reducing noise. positive changes on all scales would express recovery. In order to assess the participant’s motor function within AEMF, we calculated three performance descriptors for each extremity: http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 4 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al (1) the work area was defined as the dorsal surface area of the Finally, we compared the Stimulation Efficacy (SE) and the movement space, while (2) finger flexion, and (3) extension centroid location of the cortical motor areas representing APB were defined as the maximal and minimal metacarpal angles and ECR in M1, for the pathological and non-pathological respectively, averaged across all fingers. hemispheres (Wilcoxon sign-sum test). In order to extract training effects, we performed a within-subject analysis of the We tested AEMF sensitivity by examining between-limbs Stimulation Efficacy and the centroid location of the cortical differences in descriptor values (ie, covered area, finger flexion maps in M1 before and after treatment (Wilcoxon sign-sum and finger extension) for each subject (Wilcoxon signed-rank test). We used a Spearman test to study the correlations between test). Next, in order to explore AEMF test-retest stability and NBS outcome measures and improvements in clinical scales. sensitivity to capture improvement, we analyzed changes in descriptor values across sessions (Friedman test). In addition, Two-sided significance level for all statistical tests was defined we studied the relation between standardized clinical scores and as alpha=0.05.Data processing and statistical analysis were AEMF measurements of motor function by computing a performed using Matlab 2013a (MathWorks, Inc.). Due to Spearman correlation coefficient for each descriptor and clinical limited statistical power, we did not correct for multiple scale at the corresponding evaluation period. comparisons. Table 1. Participants’ demographics and scores from clinical scales at baseline. Demographics RGS (n=17) Control (n=18) P value Gender (female), n (%) 9 (53) 12 (67) Age, mean (SD) 65.05 (10.33) 61.75 (12.94) Affected side (left), n (%) 11 (65) 9 (50) Type (hemorrhagic), n (%) 6 (33) 6 (33) c d e a 4/3/4 6/2/4 Oxford class (LA C /PAC /TAC ) .65 Days after strok e, mean (SD) 1073.43 (767.74) 798.06 (421.80) MMSE [ 16], mean (SD) 28.24 (2.33) 28.22 (2.34) Hamilton [ 17], mean (SD) 3.71 (3.35) 4.56 (3.24) Grip force, mean (SD) 6.15 (5.04) 5.94 (5.85) f b 3.47 (0.51) 3.39 (0.61) MRC proximal [ 19], mean (SD) .76 MRC distal [ 19], mean (SD) 2.82 (1.19) 3.17 (0.99) FMA [ 20], mean (SD) 42.94 (14.37) 43.44 (13.48) g b 52.82 (23.10) 53.50 (22.51) CAHAI [21], mean (SD) .95 Barthel [ 22], mean (SD) 89.53 (9.43) 84.72 (14.19) Ashworth proximal [ 23], mean (SD) 1.24 (1.25) 1.22 (1.31) Ashworth distal [ 23], mean (SD) 1.47 (1.51) 1.00 (1.41) h b 1.59 (2.76) 2.61 (2.64) VAS shoulder [ 16], mean (SD) .13 Chi-square test. Wilcoxon rank-sum test. LAC: Lacunar stroke. PAC: Partial anterior circulation stroke. TAC: Total anterior circulation stroke. MRC: Medical Research Council. CAHAI: Chedoke Arm and Hand Activity Inventory (version CAHAI-13). VAS: Visual Analog Scale. http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 5 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al during training. Differences in performance showed a trend Results toward significance in Grasp and Place subtasks (P<.06, Wilcoxon). Notice that in order to provide an optimal training Benefits of At-Home VR-Based Training on Motor challenge for the user, the RGS system dynamically adjusted Recovery the difficulty parameters for each arm, mean performance ratios In order to assess the impact of the RGS treatment, we were maintained around 0.7 for each limb, across all tasks and conducted a repeated measures analysis of the functional sessions. Therefore these differences in performance between recovery captured through standardized clinical scales. Analysis limbs may uncover existing floor effects in the difficulty of participants’ demographics revealed no significant differences adaptation algorithm for those participants unable to achieve between groups at baseline (Table 1). Comparing the change complete power grasp movements [19]. In line with these between baseline and week 3 in clinical scores we detected a findings, a within-subject analysis revealed a significant increase significant difference on the CAHAI scale (Table 2). The RGS in the range and size difficulty coefficients assigned to the group showed significant improvements in CAHAI as compared paretic limb during the Grasp and Place task across sessions to the control group (P=.05, Wilcoxon signed-rank test, Table (P<.05, Friedman). Similar improvements were observed for 2). A post-hoc power analysis was conducted to determine the the non-paretic limb during the Hit and the Grasp subtasks. power of this statistical comparison for the sample size n=17. Automated Evaluation of Motor Function A medium effect size, d=0.48, at alpha=0.05 reached a low power level (Beta=0.4). A within-subjects analysis on the RGS In order to study the RGS AEMF sensitivity, we compared group revealed an average improvement of 1.53 (SD 2.4) points measurements for the paretic and non-paretic limb. In addition, on the CAHAI scale (P=.03, Wilcoxon signed-rank test); we explored the test-retest stability of these parameters. We however, these effects did not persist at the week 12 follow-up observed that estimates of working area and maximal finger evaluation. At follow-up we observed a significant difference extension performed by the paretic limb in AEMF were between groups in improvement on the Ashworth scale only significantly lower when compared to the non-paretic limb for distal muscle groups (P=.03, power=0.6, Wilcoxon (P<.01, Wilcoxon). Within-subjects analysis showed no effect signed-rank test), however, this difference did not reach of time in the work area for the non-paretic (P=.06, Friedman), statistical significance after Bonferroni correction. and a significant effect for the paretic limb (P=.03, Friedman). Post-hoc analysis revealed that these gains occurred during Progress of Performance in VR week 3 (P<.01, Wilcoxon). We also found a significant effect Participants in the RGS group completed a variable total number of time on maximum finger flexion for the paretic limb (P=.006, of Hit (37.1, SD 18.4), Grasp (35.1, SD 17.0) and Place (34.2, Friedman), which occurred at week 2 and 3 (P<.01, Wilcoxon, SD 16.8) subtasks along the 3 weeks of treatment. All patients Figure 3). In order to validate AEMF, we correlated its participating in the study were able to put the gloves on with measurements with assessments from standard clinical scales assistance, and autonomously set-up and use the system until (Table 2). We used AEMF-derived improvement descriptors to finishing the game. In order to assess whether the adaptive fit scores from the CAHAI scale. An optimal fit was achieved difficulty controller effectively provided customized training by the sum of maximal finger flexion and extension intensities that matched the participants’ capabilities, we (R-squared=.602, P<.001). explored inter-limb differences in mean performance ratios Figure 3. A: AEMF captures an improvement in finger flexion during treatment. Averaged movement profile of fingers excursion performed by one subject during one of the sessions. Units of finger flexion are expressed as a ratio of complete flexion. B: Mean changes in maximal finger flexion for all subjects in the RGS group across the three weeks of intervention, for both non-paretic (NPL) and paretic limbs (PL). http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 6 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al Table 2. Effects of RGS treatment versus control on clinical scales within and between groups for the post treatment assessment at week 3 and the long-term follow up at week 12. Assessment RGS (n=17) Control (n=18) Between Groups Effect size Improvement, P Improvement, mean (SD) P P Cohen d mean (SD) End (W eek 3) 0.35 (1.62) .43 1.22 (3.84) .15 .33 −0.30 UE-FM 1.53 (2.4) .01 −0.67 (6.01) .90 .05 0.48 CAHAI Barthel 0.00 (1.87) >.99 1.00 (2.87) .25 .44 −0.41 0.06 (0.24) >.99 0.11 (0.32) .50 .61 −0.17 MRCp 0.06 (0.43) >.99 0.11 (0.47) .63 .74 −0.12 MRCd 0.00 (0.35) >.99 0.06 (0.24) >.99 .32 0.40 Asp 0.12 (0.33) .50 0.00 (0.34) >.99 .32 0.36 Asd Grip force 0.41 (1.78) .89 0.38 (2.65) .47 .57 0.01 Hamilton 0.88 (2.45) .16 0.67 (1.57) .13 .66 0.10 0.41 (1.81) .05 −0.28 (1.90) .69 .63 0.37 VAS-S Follow-up (Week 12) UE-FM −0.18 (3.50) .82 1.39 (3.63) .11 .21 0.34 CAHAI −0.06 (6.51) .74 0.44 (5.46) .67 .61 −0.08 Barthel −3.30 (8.09) .29 −0.11 (3.98) .92 .74 −0.50 MRCp −0.12 (0.78) >.99 0.28 (0.46) .06 .06 −0.62 MRCd 0.29 (0.77) .25 0.17 (0.62) 45 .98 −0.17 Asp 0.06 (0.65) >.99 0.00 (0.34) >.99 >.99 −0.12 0.29 (0.59) .13 0.00 (0.00) >.99 .03 0.70 Asd Grip force 0.21 (1.45) .73 0.23 (3.02) .92 .93 −0.01 Hamilton 0.35 (2.34) .70 1.11 (3.53) .42 .93 −0.25 VAS-S 0.12 (2.06) .92 0.78 (3.08) .38 .27 −0.25 UE-FM: The upper extremity Fugl-Meyer Assessment. CAHAI: Chedoke Arm and Hand Activity Inventory (version CAHAI-13). MRCp: Medical Research Council for proximal muscles. MRCd: Medical Research Council for distal muscles. Asp: Ashworth Scale for proximal muscles. Asd: Ashworth Scale for distal muscles. VAS-S: Visual Analog Scale for Shoulder Pain. hemispheres along the mediolateral, and the anteroposterior RGS Induced Changes in the Corticospinal System axis (P<.05, Wilcoxon). In the non-pathological hemisphere, In order to detect training-induced changes in the corticospinal the cortical substrate representing the ECR was significantly system, we first characterized cortical regions in the primary larger than the area corresponding to the APB muscle (P<.05, motor area of the pathological and non-pathological hemispheres Wilcoxon). Interestingly, this difference was not present in the representing abductor pollicis brevis (APB) and extensor-carpi pathological hemisphere. radialis (ECR) muscles. At baseline, the Stimulation Efficacy SE increased significantly within subject after treatment in the (SE) was significantly higher for the non-pathological pathological hemisphere (3.6, SD 8.60; P<.01, Wilcoxon). This hemisphere when compared to the pathological one (P<.01, change was significant only for the RGS group (4.17, SD 9.86; Wilcoxon) (Figure 4). We observed that the centroid of the cortical area that produced MEPs was different between http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 7 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al P<.01, Wilcoxon; d=.6) and the APB muscle (5.21, SD 10.98; CAHAI (r =.92, P<.01), and Barthel (r =.68, P<.05), while the s s P=.05, Wilcoxon; d=.66) [29]. same effect was not present in the ECR muscle (r <.61, P>.14). In addition, centroid displacements measured after intervention We observed a centroid displacement in the pathological for the APB muscle were strongly correlated with UE-FM hemisphere, which occurred after treatment both for the APB (r =.87, P<.05), CAHAI (r =.99, P<.01), and Barthel (r =.81, s s s and the ECR muscle (Figure 4). Since changes in cortical P<.05). Centroid displacements for the ECR muscle also showed organization may indicate actual motor gains, we correlated strong correlations with UE-FM (r =.99, P<.01), and CAHAI post-treatment changes in SEs and centroid displacements with improvements at week 3 that were captured by the clinical scales (r =.89, P<.05) clinical scales. Changes in the area of the cortical [30]. Changes in SEs for the APB muscle strongly correlated regions associated with each of the two muscles did not show with improvements in UE-FM (r =.86, P<.01) (Figure 4), s any significant correlation with the improvements in clinical scales. Figure 4. Effects of domiciliary rehabilitation therapy on corticospinal efficacy. (A) Change in mean Stimulation Efficacy for extensor-carpi radialis (ECR) in the damaged hemisphere (pathological) and the intact hemisphere (non-pathological). (B) Change in mean Stimulation Efficacy for abductor pollicis brevis (APB). (C) Centroid displacements after therapy along anterioposterior and mediolateral axis. (D) Correlation of absolute centroid displacements after therapy with improvement in CAHAI score after therapy. First, we validated the RGS Adaptive Difficulty Controller, Discussion which automatically provides for a limb specific customization of practice difficulty and intensity, and a progress-monitoring Principal Findings tool. We observed lower success rates during the execution of We have studied the effectiveness of the RGS VR-based system those subtasks involving distal movements (ie, Grasp and Place). for home-based motor rehabilitation of the upper extremities Lateralized customization of task difficulty allowed for the after stroke by conducting a controlled, longitudinal clinical maintenance of optimal performance levels for each limb across trial assessing both functional and structural impact and sessions. Within-subject analysis of the evolution of the comparing it to an OT task. We have shown that, at the chronic difficulty parameters assigned during training revealed paretic stage post-stroke, the remote delivery of customized limb specific functional improvements during a reaching and self-managed motor training in VR environments may grasping task. These observations may indicate functional gains effectively induce motor gains and neuroplastic changes. of distal function (ie, increased control in fingers flexion and Comparisons between groups suggest a superiority of VR extension). Data collected by the Automated Evaluation of compared with OT in domiciliary setups, however, this Motor Function further confirmed these findings, revealing difference does not reach clinical impact. Our results highlight significant improvements for the paretic limb, during week 2 the potential of automated rehabilitation technologies for and 3, in finger flexion. Interestingly, we also found an domiciliary neurorehabilitation, which so far has been an issue improvement in range of movement both for the paretic and of some contention [31]. non-paretic limb, probably indicating a generalization of new http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 8 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al cognitive and compensatory strategies. Notice that subjects organization, the severity of hemiparesis is often greatest in the included in this study were in the chronic phase of stroke (mean distal muscles and least in the proximal muscles of the upper time post stroke 65.05 months, SD 10.3), a period in which extremity [42]. Interestingly, this disparity may only appear at motor improvements are supposed to have plateaued and limited the chronic stage [18]. Consistent with these observations, non-compensatory functional gains can still be induced through participants showed a greater muscle weakness at baseline for further physical or OT [32]. We show that the RGS group distal than for proximal muscle groups (Table 1), which may displayed significant gains on the CAHAI scale as compared be associated with a distal to proximal recovery process at this to control. However, these changes did not reach the minimal later stage post-stroke [43]. The specific factors involved in detectable change (MDC=6.3 points) and we observed no causing the observed RGS-derived improvements in distal retention of the improvements at follow-up, suggesting that function as compared to OT are not fully explained by our achievement and retention of clinically relevant improvements results. For instance, training in these two conditions differed at the chronic stage post-stroke may depend on longer in some aspects. On the one hand, RGS explicitly prevented the intervention periods [30]. We did not observe any significant execution of compensatory body movements by capturing only changes in the UE-FM scale, in any of the groups, perhaps due joint flexion and extension and filtering out the participant’s to the lack of responsiveness of this scale at the chronic stage trunk movements [44]. In contrast, participants in the control post-stroke [33]. An alternative explanation for the lack of effect group, who followed a domiciliary OT protocol, without any in the UE-FM scale is that these improvements may be supervision, may not have reached sufficient training intensity fundamentally related to compensatory changes at the Body or may have reinforced the execution of functional Functions and Structure and Activity levels [34]. compensatory movements (eg, overusing the non-paretic limb or performing trunk displacements) [45]. On the other hand, Results from the NBS protocol supported these findings by participants assigned to the RGS group repeatedly performed displaying an enhanced corticospinal excitability after treatment goal-oriented visuomotor transformations in order to control only for the more distal muscle (ABP) associated with hand the virtual analogue of their paretic and non-paretic limbs, which function. In addition, we observed centroid displacements of may induce increased neural activity in cortical motor areas the cortical map for both the ABP and the ECR. This confirms [40,46]. Indeed, we have shown that in healthy controls exposure earlier reports that enhanced corticospinal excitability and to the RGS scenario leads to significantly enhance activity in cortical map centroid displacements strongly correlate with premotor areas [47]. The OT group, however, was not exposed functional gains detected by standardized clinical scales, such to such transformations, indeed subjects in this group performed as Fugl-Meyer, CAHAI, and Barthel scales [30,32,35-37]. repetitive visuomotor tasks in the real world only, where visual Previous research suggests that an imaging measure of exposure to motor movements performed with the paretic limb corticospinal tract (CST) injury in the acute phase can predict may not be critical for successful performance. Although these motor outcome at 3 months [38]. Our results show that are factors that could be better controlled in OT, our objective NBS-derived measures of corticospinal connectivity may be was to achieve a fair comparison between RGS virtual reality also relevant biomarkers for identifying chronic stroke survivors based and standard domiciliary OT and to understand their who have the potential to respond to a particular rehabilitative relative impact. In addition to motor gains, we observed a therapy and may be predictive of patient prognosis. Overall, reduction in shoulder pain in the VR group, captured by the these plastic changes may be use-dependent; an increase in the VAS scale. The reason for this effect may be that the VR group use of the paretic limb during the intervention period may have did not have to perform repetitive movements at the shoulder unmasked preexisting excitatory connections or even enhanced joint, unlike the control group. This difference could also explain the efficacy of existing neuronal networks. Thus, RGS-induced the trend in an increase in muscle strength for the proximal cortical changes could be related to a greater activation in the musculature in the control group. ipsilesional hemisphere, as has been proposed by previous studies [39,40]. Conclusions In this randomized controlled study, we explored the effects of Limitations a VR-based system for domiciliary rehabilitation on functional Taking a global perspective on these results, we observe that recovery and cortical reorganization. Our results suggest that task difficulty descriptors, AEMF measurements, and NBS, at-home VR-based rehabilitation promotes functional motor converged, suggesting that distal functional improvements were gains, enhances corticospinal excitability, and induces cortical induced through RGS based training and were significantly reorganization at the chronic stage post- stroke. The observation larger for those participants in the RGS group when compared of strong correlations between increased motor evoked potentials with the control group. The reason why we may not have after treatment and functional gains in CAHAI suggests that observed improvements in proximal muscle groups and other exposure to VR-based goal-oriented motor training may have clinical scales may be related to the stringent inclusion criteria enhanced the organization of corticospinal pathways, facilitating of the study, which excluded all subjects showing severe distal motor control. The displacement of the centroid of cortical hemiparesis at baseline (Proximal Medical Research Council, maps after training may also indicate related cortical MRC>2). It is widely known that the corticospinal system is reorganization at the chronic stage post-stroke supporting the organized following a proximal to distal gradient to the cervical idea that recovery can be induced at any stage post stroke albeit spinal cord, where motoneurons of the distal muscle groups to varying degrees. receive most input projections [41]. Due to this hierarchical http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 9 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al Acknowledgments We would like to thank all subjects who participated in this study. We also would like to gratefully acknowledge Estefanía Montiel for her assistance in recruiting and evaluating the participants. This work was supported by the MINECO “Retos Investigacion tos Investigacion I + D + I” Plan Nacional project SANAR (Gobierno de España), and the European Research Council under grant agreement 341196 CDAC and FP7-ICT- 270212 project eSMC. Conflicts of Interest PV is involved in the spin-off company Eodyne Systems SL, which has the goal to achieve a large-scale distribution of science based rehabilitation technologies. Multimedia Appendix 1 CONSORT eHealth form. [PDF File (Adobe PDF File), 66KB-Multimedia Appendix 1] References 1. Shah S, Vanclay F, Cooper B. Predicting discharge status at commencement of stroke rehabilitation. Stroke 1989 Jun 01;20(6):766-769. [doi: 10.1161/01.STR.20.6.766] 2. Lai S, Studenski S, Duncan P, Perera S. Persisting consequences of stroke measured by the Stroke Impact Scale. Stroke 2002 Jul;33(7):1840-1844 [FREE Full text] [Medline: 12105363] 3. Shaughnessy M, Resnick B, Macko R. Testing a model of post-stroke exercise behavior. Rehabil Nurs 2006;31(1):15-21. [Medline: 16422040] 4. Hopman W, Verner J. Quality of life during and after inpatient stroke rehabilitation. Stroke 2003 Feb 13;34(3):801-805 [FREE Full text] [doi: 10.1161/01.STR.0000057978.15397.6F] 5. Anderson C, Mhurchu C, Rubenach S, Clark M, Spencer C, Winsor A. Home or hospital for stroke Rehabilitation? results of a randomized controlled trial : II: cost minimization analysis at 6 months. Stroke 2000 May;31(5):1032-1037 [FREE Full text] [Medline: 10797162] 6. Widén HL, von KL, Kostulas V, Holm M, Widsell G, Tegler H, et al. A randomized controlled trial of rehabilitation at home after stroke in southwest Stockholm. Stroke 1998 Mar;29(3):591-597 [FREE Full text] [Medline: 9506598] 7. Simpson L, Eng J, Chan M. H-GRASP: the feasibility of an upper limb home exercise program monitored by phone for individuals post stroke. Disabil Rehabil 2017 May;39(9):874-882 [FREE Full text] [doi: 10.3109/09638288.2016.1162853] [Medline: 27017890] 8. Mayo N, Wood-Dauphinee S, Côté R, Gayton D, Carlton J, Buttery J, et al. There's no place like home : an evaluation of early supported discharge for stroke. Stroke 2000 May;31(5):1016-1023 [FREE Full text] [Medline: 10797160] 9. Garrido NJ, Ruiz PV, Lozano PM. Movement-based interaction applied to physical rehabilitation therapies. J Med Internet Res 2014 Dec 09;16(12):e281 [FREE Full text] [doi: 10.2196/jmir.3154] [Medline: 25491148] 10. Hillier S, Inglis-Jassiem G. Rehabilitation for community-dwelling people with stroke: home or centre based? a systematic review. Int J Stroke 2010 Jun;5(3):178-186. [doi: 10.1111/j.1747-4949.2010.00427.x] [Medline: 20536615] 11. Rose F, Brooks B, Rizzo A. Virtual reality in brain damage rehabilitation: review. Cyberpsychol Behav 2005 Jun;8(3):241-62; discussion 263. [doi: 10.1089/cpb.2005.8.241] [Medline: 15971974] 12. Lewis G, Rosie J. Virtual reality games for movement rehabilitation in neurological conditions: how do we meet the needs and expectations of the users? Disabil Rehabil 2012;34(22):1880-1886. [doi: 10.3109/09638288.2012.670036] [Medline: 22480353] 13. Cameirão MS, Badia SB, Duarte E, Frisoli A, Verschure PF. The combined impact of virtual reality neurorehabilitation and its interfaces on upper extremity functional recovery in patients with chronic stroke. Stroke 2012 Oct;43(10):2720-2728 [FREE Full text] [doi: 10.1161/STROKEAHA.112.653196] [Medline: 22871683] 14. McEwen D, Taillon-Hobson A, Bilodeau M, Sveistrup H, Finestone H. Virtual reality exercise improves mobility after stroke: an inpatient randomized controlled trial. Stroke 2014 Jun;45(6):1853-1855 [FREE Full text] [doi: 10.1161/STROKEAHA.114.005362] [Medline: 24763929] 15. Rizzo A. Virtual reality and disability: emergence and challenge.  Disabil Rehabil 2009 Jul 07;24(11-12):567-569 [FREE Full text] [doi: 10.1080/09638280110111315] 16. Cameirão MS, Badia SB, Oller ED, Verschure PF. Neurorehabilitation using the virtual reality based rehabilitation gaming system: methodology, design, psychometrics, usability and validation. J Neuroeng Rehabil 2010 Sep 22;7:48 [FREE Full text] [doi: 10.1186/1743-0003-7-48] [Medline: 20860808] 17. Dickstein R, Deutsch J. Motor imagery in physical therapist practice. Phys Ther 2007 Jul;87(7):942-953. [doi: 10.2522/ptj.20060331] [Medline: 17472948] 18. Lang CE, Wagner JM, Bastian AJ, Hu Q, Edwards DF, Sahrmann SA, et al. Deficits in grasp versus reach during acute hemiparesis. Exp Brain Res 2005 Sep;166(1):126-136. [doi: 10.1007/s00221-005-2350-6] [Medline: 16021431] http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 10 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al 19. Nirme J, Duff A, Verschure PF. Adaptive rehabilitation gaming system: on-line individualization of stroke rehabilitation. Conf Proc IEEE Eng Med Biol Soc 2011;2011:6749-6752. [doi: 10.1109/IEMBS.2011.6091665] [Medline: 22255888] 20. Csikszentmihalyi M. Flow: the classic work on how to achieve happiness. London: Rider; 2002. 21. Gladstone D, Danells C, Black S. The fugl-meyer assessment of motor recovery after stroke: a critical review of its measurement properties. Neurorehabil Neural Repair 2002 Sep;16(3):232-240. [doi: 10.1177/154596802401105171] [Medline: 12234086] 22. Barreca S, Stratford P, Lambert C, Masters L, Streiner D. Test-retest reliability, validity, and sensitivity of the Chedoke arm and hand activity inventory: a new measure of upper-limb function for survivors of stroke. Arch Phys Med Rehabil 2005 Aug;86(8):1616-1622. [doi: 10.1016/j.apmr.2005.03.017] [Medline: 16084816] 23. Collin C, Wade D, Davies S, Horne V. The Barthel ADL Index: a reliability study. Int Disabil Stud 1988;10(2):61-63. [Medline: 3403500] 24. Bohannon RW, Smith MB. Interrater reliability of a modified Ashworth scale of muscle spasticity. Phys Ther 1987 Feb;67(2):206-207. [Medline: 3809245] 25. Wadsworth CT, Krishnan R, Sear M, Harrold J, Nielsen DH. Intrarater reliability of manual muscle testing and hand-held dynametric muscle testing. Phys Ther 1987 Sep;67(9):1342-1347. [Medline: 3628487] 26. Knesevich JW, Biggs JT, Clayton PJ, Ziegler VE. Validity of the Hamilton rating Scale for depression. Br J Psychiatry 1977 Jul;131:49-52. [Medline: 884416] 27. Bijur P, Silver W, Gallagher E. Reliability of the visual analog scale for measurement of acute pain. Acad Emerg Med 2001 Dec;8(12):1153-1157 [FREE Full text] [Medline: 11733293] 28. Ruohonen J, Karhu J. Navigated transcranial magnetic stimulation. Neurophysiol Clin 2010 Mar;40(1):7-17. [doi: 10.1016/j.neucli.2010.01.006] [Medline: 20230931] 29. Dunlap W, Cortina JM, Vaslow J, Burke M. Meta-analysis of experiments with matched groups or repeated measures designs.  Psychol Methods 1996;1(2):170-177. [doi: 10.1037/1082-989X.1.2.170] 30. Liepert J, Miltner W, Bauder H, Sommer M, Dettmers C, Taub E, et al. Motor cortex plasticity during constraint-induced movement therapy in stroke patients. Neurosci Lett 1998 Jun 26;250(1):5-8. [Medline: 9696052] 31. Coupar F, Pollock A, Legg LA, Sackley C, van Vliet P. Home-based therapy programmes for upper limb functional recovery following stroke. Cochrane Database Syst Rev 2012 May 16(5):CD006755. [doi: 10.1002/14651858.CD006755.pub2] [Medline: 22592715] 32. Murphy T, Corbett D. Plasticity during stroke recovery: from synapse to behaviour. Nat Rev Neurosci 2009 Dec;10(12):861-872. [doi: 10.1038/nrn2735] [Medline: 19888284] 33. Nudo R, Milliken G, Jenkins W, Merzenich M. Use-dependent alterations of movement representations in primary motor cortex of adult squirrel monkeys. J Neurosci 1996 Jan 15;16(2):785-807 [FREE Full text] [Medline: 8551360] 34. Levin MF, Kleim JA, Wolf SL. What do motor recovery and compensation mean in patients following stroke? Neurorehabil Neural Repair 2009 May;23(4):313-319. [doi: 10.1177/1545968308328727] [Medline: 19118128] 35. Zhu LL, Lindenberg R, Alexander MP, Schlaug G. Lesion load of the corticospinal tract predicts motor impairment in chronic stroke. Stroke 2010 May;41(5):910-915 [FREE Full text] [doi: 10.1161/STROKEAHA.109.577023] [Medline: 20378864] 36. Thickbroom GW, Byrnes ML, Archer SA, Mastaglia FL. Motor outcome after subcortical stroke correlates with the degree of cortical reorganization. Clin Neurophysiol 2004 Sep;115(9):2144-2150. [doi: 10.1016/j.clinph.2004.04.001] [Medline: 15294217] 37. Kim Y, You SH, Ko M, Park J, Lee KH, Jang SH, et al. Repetitive transcranial magnetic stimulation-induced corticomotor excitability and associated motor skill acquisition in chronic stroke. Stroke 2006 Jun;37(6):1471-1476 [FREE Full text] [doi: 10.1161/01.STR.0000221233.55497.51] [Medline: 16675743] 38. Yu X, Song R, Jiaerken Y, Yuan L, Huang P, Lou M, et al. White matter injury induced by diabetes in acute stroke is clinically relevant: a preliminary study. Diab Vasc Dis Res 2017 Jan;14(1):40-46. [doi: 10.1177/1479164116675491] [Medline: 27941055] 39. Sung H, You S, Hallett M, Yun W, Park C, Cho S. Cortical reorganization and associated functional motor recovery after virtual reality in patients with chronic stroke: An experimenter-blind preliminary study. Arch Phys Med Rehabil 2005;86(11):2218-2223. [Medline: 16271575] 40. Saleh S, Adamovich SV, Tunik E. Mirrored feedback in chronic stroke: recruitment and effective connectivity of ipsilesional sensorimotor networks. Neurorehabil Neural Repair 2014 May;28(4):344-354 [FREE Full text] [doi: 10.1177/1545968313513074] [Medline: 24370569] 41. Clough J, Kernell D, Phillips C. The distribution of monosynaptic excitation from the pyramidal tract and from primary spindle afferents to motoneurones of the baboon's hand and forearm. J Physiol 1968 Sep;198(1):145-166 [FREE Full text] [Medline: 16992310] 42. Colebatch J, Gandevia S. The distribution of muscular weakness in upper motor neuron lesions affecting the arm. Brain 1989 Jun;112 (Pt 3):749-763. [Medline: 2731028] http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 11 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Ballester et al 43. Lambercy O, Dovat L, Yun H, Wee SW, Kuah CW, Chua KS, et al. Effects of a robot-assisted training of grasp and pronation/supination in chronic stroke: a pilot study. J Neuroeng Rehabil 2011 Nov 16;8:63 [FREE Full text] [doi: 10.1186/1743-0003-8-63] [Medline: 22087842] 44. Cameirão MS, Badia SB, Duarte E, Frisoli A, Verschure PF. The combined impact of virtual reality neurorehabilitation and its interfaces on upper extremity functional recovery in patients with chronic stroke. Stroke 2012 Oct;43(10):2720-2728 [FREE Full text] [doi: 10.1161/STROKEAHA.112.653196] [Medline: 22871683] 45. Michaelsen S, Dannenbaum R, Levin M. Task-specific training with trunk restraint on arm recovery in stroke: randomized control trial. Stroke 2006 Jan;37(1):186-192 [FREE Full text] [doi: 10.1161/01.STR.0000196940.20446.c9] [Medline: 16339469] 46. Tunik E, Saleh S, Bagce H, Merians A, Adamovich SV. Mirror feedback in virtual reality elicits ipsilesional motor cortex activation in chronic stroke patients. 2011 Jun 27 Presented at: Int Conf Virtual Rehabilitation ICVR; 2011; Zurich URL: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5971862 [doi: 10.1109/ICVR.2011.5971862] 47. Seitz R, Huang Y, Knorr U, Tellmann L, Herzog H, Freund HJ. Large-scale plasticity of the human motor cortex. Neuroreport 1995 Mar 27;6(5):742-744. [Medline: 7605938] Abbreviations AEMF: automated evaluation of motor function APB: abductor pollicis brevis ASd: Ashworth scale for distal upper limb ASp: Ashworth scale for proximal upper limb BI: barthel index CAHAI: chedoke arm and hand activity inventory ECR: extensor-carpi radialis MMSE: mini-mental state evaluation MRC: medical research council scale NBS: navigated brain stimulation OT: occupational therapy RGS: rehabilitation gaming system SE: simulation efficacy UE-FM: the upper extremity Fugl-Meyer assessment VAS: visual analog scale VR: virtual reality Edited by G Eysenbach; submitted 09.10.16; peer-reviewed by I Cikajlo, R Lloréns, D Putrino; comments to author 09.01.17; revised version received 04.04.17; accepted 29.04.17; published 07.08.17 Please cite as: Ballester BR, Nirme J, Camacho I, Duarte E, Rodríguez S, Cuxart A, Duff A, Verschure PF Domiciliary VR-Based Therapy for Functional Recovery and Cortical Reorganization: Randomized Controlled Trial in Participants at the Chronic Stage Post Stroke JMIR Serious Games 2017;5(3):e15 URL: http://games.jmir.org/2017/3/e15/ doi: 10.2196/games.6773 PMID: 28784593 ©Belén Rubio Ballester, Jens Nirme, Irene Camacho, Esther Duarte, Susana Rodríguez, Ampar Cuxart, Armin Duff, Paul F.M.J. Verschure. Originally published in JMIR Serious Games (http://games.jmir.org), 07.08.2017. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Serious Games, is properly cited. The complete bibliographic information, a link to the original publication on http://games.jmir.org, as well as this copyright and license information must be included. http://games.jmir.org/2017/3/e15/ JMIR Serious Games 2017 | vol. 5 | iss. 3 | e15 | p. 12 (page number not for citation purposes) XSL FO RenderX

Journal

JMIR Serious GamesJMIR Publications

Published: Aug 7, 2017

Keywords: stroke; movement disorder; recovery of function, neuroplasticity; transcranial magnetic stimulation; physical therapy; hemiparesis; computer applications software

There are no references for this article.