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Effects of virtual reality-based rehabilitation on distal upper extremity function and health-related quality of life: a single-blinded, randomized controlled trial

Effects of virtual reality-based rehabilitation on distal upper extremity function and... Background: Virtual reality (VR)-based rehabilitation has been reported to have beneficial effects on upper extremity function in stroke survivors; however, there is limited information about its effects on distal upper extremity function and health-related quality of life (HRQoL). The purpose of the present study was to examine the effects of VR-based rehabilitation combined with standard occupational therapy on distal upper extremity function and HRQoL, and compare the findings to those of amount-matched conventional rehabilitation in stroke survivors. Methods: The present study was a single-blinded, randomized controlled trial. The study included 46 stroke survivors who were randomized to a Smart Glove (SG) group or a conventional intervention (CON) group. In both groups, the interventions were targeted to the distal upper extremity and standard occupational therapy was administered. The primary outcome was the change in the Fugl–Meyer assessment (FM) scores, and the secondary outcomes were the changes in the Jebsen–Taylor hand function test (JTT), Purdue pegboard test, and Stroke Impact Scale (SIS) version 3.0 scores. The outcomes were assessed before the intervention, in the middle of the intervention, immediately after the intervention, and 1 month after the intervention. Results: The improvements in the FM (FM-total, FM-prox, and FM-dist), JTT (JTT-total and JTT-gross), and SIS (composite and overall SIS, SIS-social participation, and SIS-mobility) scores were significantly greater in the SG group than in the CON group. Conclusions: VR-based rehabilitation combined with standard occupational therapy might be more effective than amount-matched conventional rehabilitation for improving distal upper extremity function and HRQoL. Trial registration: This study is registered under the title “Effects of Novel Game Rehabilitation System on Upper Extremity Function of Patients With Stroke” and can be located in https://clinicaltrials.gov with the study identifier NCT02029651. Keywords: Rehabilitation, Upper extremity, Virtual reality therapy, Quality of life, Video games * Correspondence: [email protected] National Rehabilitation Center, Ministry of Health and Welfare, Seoul, Korea Department of Rehabilitation Medicine, National Rehabilitation Center, Ministry of Health and Welfare, Samgaksan-ro 58, Gangbuk-gu, Seoul 142-884, Korea Full list of author information is available at the end of the article © 2016 Shin et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 2 of 10 Background Methods Regaining upper extremity function is one of the Study design major goals in stroke survivors, as it is important for The present study was a single-blinded, randomized con- performing activities of daily living (ADLs). However, trolled trial performed at National Rehabilitation Center, approximately 80 % of stroke survivors have upper ex- an urban rehabilitation hospital in Seoul, Korea. Eligible tremity limitations, and these limitations persist in ap- participants were randomly assigned to a Smart Glove proximately half of these survivors in the chronic (SG) or conventional intervention (CON) group using a phase [1, 2]. Distal upper extremity function is vital computer-generated randomized scheme. The allocation for performing ADLs, such as holding objects like was performed using sealed opaque envelopes with the utensils, turning a doorknob or key in a lock, tele- group name, which were placed in a plastic container in phone or computer use, and writing, and is strongly numerical order. Randomization, outcome measurements, related to quality of life (QoL) in stroke survivors [3]. and data analysis were performed by different individuals In stroke survivors, the distal upper extremity is se- who were not involved in the intervention. This study was verely affected and is the last body part to recover [4]. registered at clinicaltrials.gov (NCT02029651) and was ap- Therefore, improving distal upper extremity function proved by the Ethics Committee of the National Rehabili- is of primary importance in the rehabilitation of stroke tation Center, Korea. All participants provided informed survivors. written consent before enrollment. Recent studies have emphasized the use of interven- tions that are focused and repetitive, relevant to real-life, Participants and actively performed in order to promote cortical The study included 46 consecutive participants with upper reorganization and neuroplasticity [5–8]. In this context, extremity functional deficits caused by stroke, who were conventional interventions have been complemented by present in a rehabilitation hospital. The inclusion criteria novel technologies such as virtual reality (VR). were as follows: (1) first-ever ischemic or hemorrhagic VR-based rehabilitation is promising in stroke survi- stroke; (2) complaints of unilateral upper extremity func- vors, and many types of VR-based rehabilitation ap- tional deficits after stroke; and (3) presence of a score of at paratus from commercial video game equipment to least 2 points on the medical research council scale robotics are currently being developed and used. In [14] for wrist flexion/extension or forearm pronation/ the area of upper limb rehabilitation, a large number supination, as the SG system can be operated only with of studies have been performed in stroke survivors, volitional movements and does not involve external as- and a recent systematic review concluded that the use sistance. The exclusion criteria were as follows: (1) age of VR-based rehabilitation is superior to amount- <18 years; (2) uncontrolled hypertension, unstable an- matched conventional rehabilitation for improving gina, recent myocardial infarction, or any history of upper limb function [9]. Nevertheless, most studies on seizure; (3) predisposing psychological disorders that VR-based rehabilitation for the upper extremity re- could impede participation; (4) neurological disorders ported on the proximal upper extremity, with limited that cause motor deficits, such as Parkinson’sdisease information on the distal upper extremity. Although 2 and peripheral neuropathy; (5) severe aphasia resulting previous studies showed promising results regarding in communication difficulties that could influence the VR-based rehabilitation for the distal upper extremity, intervention and outcome measures; (6) cognitive im- these studies did not include a control group [10, 11]. pairment resulting in cooperation difficulties (a score of Randomized control trials have been performed using ≤24 in the Mini-Mental State Examination) [15]; and a VR system with different types of gloves; however, a (7) severe pain impeding upper extremity rehabilitation definite conclusion about the treatment effect could (numeric pain rating scale score ≥ 7) [16]. not be obtained owing to the low number of partici- pants [12, 13]. Furthermore, the effects of VR-based Intervention rehabilitation on health related quality of life (HRQoL) All participants received a 4-week face-to-face interven- have not been appropriately assessed, although the tion program (SG or CON) individually (20 sessions for QoL of stroke survivors is crucial for comprehensive 30 min per day) in a room for the intervention, as well rehabilitation. as standard OT daily for 30 min in a room for OT. The Therefore, the objective of the present study was to intervention programs exclusively focused on the distal examine the effects of VR-based rehabilitation com- upper extremity and were administered by 3 trained oc- bined with standard occupational therapy (OT) on dis- cupational therapists who were involved in both the in- tal upper extremity function and HRQoL, and compare terventions and were exclusively dedicated to this study. the findings to those of amount-matched conventional The therapists were sequentially allocated such that the rehabilitation in stroke survivors. intervention to be performed by each therapist was Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 3 of 10 automatically selected based on the randomized alloca- scores. The games simulate ADLs, such as catching tion of the SG and CON groups in order to minimize butterflies or balls, squeezing oranges, fishing, cooking, therapist bias. The intervention time was the same in cleaning the floor, pouring wine, painting fences, and both the groups. Standard OT involved range of motion turning over pages, which allows the participants to and strengthening exercises for the affected limb, table- easily familiarize themselves with the training program top activities, and training for ADLs and was adminis- and motivates them to perform the tasks. tered by occupational therapists who were not involved The intervention in the SG group involved the above- in this study. mentioned categories of movements of the distal upper extremity in order to achieve goals in a specific task Smart glove intervention based on visual feedback in real time. In addition, the The RAPAEL Smart Glove™ (Neofect, Yong-in, Korea) is a difficulty of the intervention was adjusted by the artifi- biofeedback system designed for distal upper extremity cial intelligence of the system according to participant rehabilitation in stroke survivors (Fig. 1). It includes a performance [17]. The function for the algorithm is glove-shaped sensor device and a software application. given by The sensor device tracks the motion and posture of the wearer’s distal limb and recognizes functional movements, DL ¼ DL  1 þ α P −P ð1Þ i i−1 i−1 ref such as forearm pronation/supination, wrist flexion/exten- sion, radial-ulnar deviation, and finger flexion/extension. where DL is the difficulty level for the current trial i, α is An inertial measurement unit sensor in the device mea- aconstant for therateofupdate, P is the performance t-1 sures the 3-dimensional orientation of the distal limb, and on the previous trial, and P is the reference perform- ref 5 bending sensors estimate the degree of bending of the ance. In the games, the performance in the algorithm is fingers. The gathered sensing data is transmitted and re- mostly range of motion for each function movement, but ceived via wireless communication systems such as Blue- it could be other quantity such as time depending on the tooth. The software application manipulates virtual hands games. The reference performance is set to be 80 % of the or virtual objects in training games according to the re- active range of motion or 80 % of the maximum perform- ceived data. In addition, this system can evaluate the active ance from previous trials. The difficulty level could be and passive range of motion for each functional movement. position of target, target performance, duration, move- The training games in the SG system are categorized ac- ment speed, or others depending on the game. The algo- cording to the intended movements as follows: forearm rithm progressively increases the difficulty level until the pronation/supination, wrist flexion/extension in the verti- current performance is below the reference performance, cal plane, wrist flexion/extension in the horizontal plane and it keeps modulating the difficulty level to make the with gravity eliminated, wrist radial/ulnar deviation in the performance stay near the reference performance. vertical plane, wrist radial/ulnar deviation in the horizon- tal plane with gravity eliminated, finger flexion/extension, Conventional intervention and complex movements. In each game, the wearer is The intervention in the CON group involved the same required to successfully perform a task that is related to categories of movements of the distal upper extremity as the specific intended movement in order to obtain high those in the SG group in order to minimize confounding Fig. 1 The RAPAEL Smart Glove™ system and the task-specific games of this system Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 4 of 10 between the 2 groups. Therefore, all factors, except hand (PPT-aff), both hands (PPT-both), and assembly the use of the SG system, were consistent between the (PPT-assembly). 2groups. Thedifficultyofthe interventionwasad- HRQoL was measured using a stroke-specific, self- justed by occupational therapists according to partici- reported patient-perspective assessment tool, the Stroke pant performance. Impact Scale (SIS) version 3.0, which consists of the following 8 domains: strength, hand function, mobility, physical and instrumental activities of daily living (ADLs/ Outcome measures IADLs), memory and thinking, communication, emotion, The baseline characteristics assessed were age, sex, hand- and social participation [20]. The score for each domain edness, time since stroke onset, stroke type, affected body ranges from 0 to 100, with higher scores indicating better side, and the medical research council scale scores of the HRQoL. The hand function, ADLs/IADLs, and social par- flexor/extensor of the shoulder, elbow, and wrist. ticipation scores were combined into a composite SIS score to demonstrate the comprehensive impact of func- Primary outcome tional change relevant to the interventions used in the Motor impairment of the affected upper limb was evalu- present study from the perspective of the international ated using the upper extremity Fugl–Meyer assessment classification of functioning, disability, and health [21]. (FM-total; 33 items with a 3-point ordinal scale; range, Additionally, the overall SIS score was calculated as the 0–66), with higher scores indicating lower impairment sum of all domain scores. The secondary outcomes were [18]. We further divided the FM-total score into prox- the changes in the JTT, PPT, and SIS scores. imal (shoulder, elbow, and forearm; FM-prox) and distal The FM, JTT, and PPT scores were determined before (wrist and hand; FM-dist) scores. The primary outcome the intervention (T0), in the middle of the intervention was the change in the FM scores. (after the 10th session; T1), immediately after the inter- vention (T2), and 1 month after the intervention (T3). Secondary outcomes The SIS scores were determined only at T0 and T2. A Hand function was evaluated using the Jebsen–Taylor trained and blinded outcome assessor who was unaware hand function test (JTT) and Purdue pegboard test (PPT). of group allocation performed all outcome measure- The JTT was used to assess hand function mimicking ments. Adverse events were recorded during the inter- ADLs. It involves a series of 7 timed subtests, including vention and at outcome measurements. writing, simulated page turning, picking up small objects, simulated feeding, stacking checkers, picking up large Sample size light objects, and picking up large heavy objects. Quantifi- As this was the first study to assess the efficacy of the SG cation is not possible if a subtest cannot be completed system in people with stroke, power calculation was per- within a certain time, as the result is a continuous time formed using FM scores from a previous study, which variable, and a subtest is considered to have a missing applied VR-based rehabilitation for the upper extremity in value if it cannot be completed. Therefore, we used a scor- stroke survivors, hypothesizing a similar efficacy between ing system (each subtest score ranges from 0 to 15, and our rehabilitation and the previous rehabilitation [22]. Ac- the total score calculated as the sum of each subtest score cordingly, 18 participants were required in each group to ranges from 0 to 105), which has been shown to have provide 80 % power for efficacy evaluation, setting the α good validity in people with stroke [19]. We used the total level at 0.05. Finally, we calculated that 46 participants score (JTT-total), and divided the JTT-total into gross were needed, considering a 20 % dropout rate. (stacking checkers, picking up large light objects, and picking up large heavy objects; JTT-gross) and fine hand Statistical analysis function (writing, simulated page turning, picking up An intention-to-treat analysis was performed, which in- small objects, and simulated feeding; JTT-fine) scores. cluded all participants who were enrolled in the present The PPT was used to evaluate fine hand motor profi- study regardless of intervention completion. We used the ciency. It involves a board with 2 parallel rows having 25 last observed outcome values for the determination of holes each. The participants are required to pick and missing values in dropouts, conservatively assuming that place pins into the holes, and the score is the number of no changes occurred after the last observation. At base- pins placed in 30 s. Scores are assessed for the right line, the mean values of variables were compared between hand, left hand, and both hands, and the sum of these the SG and CON groups using the Mann–Whitney U test scores is determined. The test involves 4 trials. Add- and Fisher exact test for continuous and categorical vari- itionally, scores are assessed for the number of assem- ables, respectively. Analysis of variance was performed for bled pins, washers, and collars in 60 s. We modified repeated measurements in the groups (SG and CON the original PPT, and recorded scores for the affected groups) as the between-patient factors and time (T0, T1, Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 5 of 10 T2, and T3) as the within-patient factor in order to there were no differences in the demographics and clinical compare the effects of each intervention on the FMA, characteristics between the SG and CON groups (Table 1). JTT, and PPT scores. The main effects of Group, Time, and Time × Group interactions were evaluated. The Primary outcomes Greenhouse-Geisser procedure was applied when the The FM scores of the SG and CON groups are presented assumption of sphericity was violated, and the post-hoc in Table 2. There were no differences in the FM-total, test was performed. All statistical analyses were performed FM-prox, and FM-dist scores between the 2 groups at T0. using SPSS software (version 17.0; IBM, Armonk, NY), There were significant improvements in the FM-total, and a P-value <0.05 was considered statistically significant. FM-prox, and FM-dist scores in the SG group during the intervention and at the follow-up; however, no significant changes were noted in the CON group (Fig. 3). The im- Results provements in the SG group were supported by significant Of the 46 participants included in the present study, 33 Time × Group interactions (FM-total: F = 6.48, df = 1.46, completed the 4-week intervention programs and assess- P = 0.006; FM-prox: F = 5.73, df = 1.705, P =0.007; FM- ments at T2 and 23 completed the follow-up assessments dist: F = 4.64, df = 1.38, P =0.024). at T3. During the study, 5 and 8 participants from the SG and CON groups, respectively, did not complete the inter- Secondary outcomes vention programs. The sample sizes at the assessment time Jebsen–Taylor hand function test points are presented in Fig. 2. There were no serious ad- The JTT scores of the SG and CON groups are presented verse events, and only 1 participant from the CON group in Table 2. There were no significant differences in the dropped out owing to dizziness, which was unrelated to JTT-total, JTT-gross, and JTT-fine scores between the 2 the intervention. Thus, most of the study withdrawals were groups at T0. The post-hoc test found that there were sig- related to uncooperativeness, and the number was higher nificant improvements in the JTT-total, JTT-gross, and than that hypothesized in the study design. At baseline, JTT-fine scores in the SG group during the intervention Fig. 2 Flowchart of the participants through the study. Abbreviations: SG, Smart Glove; CON, conventional intervention Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 6 of 10 Table 1 Participant Characteristics SG group (n = 24) CON group (n = 22) P-value Demographics Age, years 57.2 ± 10.3 59.8 ± 13.0 0.373 Gender, male 19 (79.2) 17 (77.3) 0.578 Dominant hand, right 23 (95.8) 22 (100) 0.522 Stroke characteristics Time from stroke, months 13.6 ± 13.4 15.0 ± 14.6 0.809 Affected arm, right 9 (37.5) 11 (50.0) 0.590 Ischemia 15 (62.5) 14 (63.6) 0.590 Clinical characteristics MRC scale shoulder flexor 3.2 ± 0.7 3.3 ± 0.7 0.738 MRC scale shoulder extensor 3.3 ± 0.6 3.4 ± 0.6 0.703 MRC scale elbow flexor 3.6 ± 0.6 3.8 ± 0.6 0.472 MRC scale elbow extensor 3.5 ± 0.6 3.7 ± 0.6 0.228 MRC scale wrist flexor 3.4 ± 0.6 3.6 ± 0.7 0.490 MRC scale wrist extensor 3.4 ± 0.7 3.5 ± 0.8 0.719 FM-total score 53.4 ± 8.7 48.2 ± 12.3 0.169 Abbreviations: SG Smart Glove, CON conventional intervention, MRC medical research council, FM Fugl–Meyer assessment Values are presented as mean ± standard deviation or number (%). There were no significant differences between groups at baseline for the characteristics Mann–Whitney U test Fisher’s exact test and at the follow-up; however, no significant changes were df = 1.547, P = 0.350), and PPT-assembly (F = 1.934, noted in the CON group (Fig. 4). The improvements in df = 2.265, P =0.288, P = 0.144) were not significant, indi- the JTT-total and JTT-gross scores in the SG group were cating a similar increase in fine hand motor function in supported by significant Time × Group interactions (JTT- both groups. total: F = 4.073, df = 1.497, P = 0.032; JTT-gross: F = 4.155, df = 1.705, P = 0.025). However, the Time × Group inter- Stroke impact scale action for the JTT-fine score was not significant, indicat- There were no significant differences in the composite, ing a similar pattern in both groups (F = 2.207, df = 1.493, overall, and individual SIS domain scores between the 2 P =0.131). groups at T0 (Table 3). The post-hoc test found that the SG group had significant improvements in the com- Perdue pegboard test posite (36.7 ± 10.0, P = 0.001) and overall SIS scores The PPT-aff, PPT-both, and PPT-assembly scores (61.0 ± 19.6, P = 0.005) during the intervention. How- were higher in the SG group than in the CON group ever, no significant improvements in the composite at T0 (P = 0.033, P = 0.018, and P = 0.009, respect- (1.9 ± 10.5, P= 0.856) and overall SIS scores (2.1 ± 15.1, ively). The Time × Group interactions for PPT-aff (F P= 0.889) were noted in the CON group. Additionally, = 1.260, df = 1.912, P = 0.288), PPT-both (F = 1.016, the Time × Group interactions were significant for the Table 2 FM and JTT Scores in the SG and CON Groups SG (n = 24) CON (n = 22) T0 T2 Change P-value T3 Change P-value T0 T2 Change P-value T3 Change P-value (T2 − T0) (T3 − T0) (T2 − T0) (T3 − T10) FM-total 53.4 ± 1.8 58.3 ± 1.7 4.9 ± 1.0 <0.001 58.5 ± 1.7 5.3 ± 1.1 0.001 48.2 ± 2.6 49.6 ± 2.7 1.4 ± 0.8 0.512 49.5 ± 2.7 1.3 ± 0.8 0.592 FM-prox 30.0 ± 1.0 32.5 ± 0.9 2.5 ± 0.6 0.001 32.7 ± 0.9 2.6 ± 0.6 0.001 28.3 ± 1.4 28.9 ± 1.4 0.6 ± 0.4 0.538 29.0 ± 1.4 0.7 ± 0.4 0.471 FM-dist 19.4 ± 0.7 21.2 ± 0.7 1.8 ± 0.5 0.004 21.2 ± 0.7 1.8 ± 0.5 0.007 17.3 ± 1.1 17.4 ± 1.1 0.3 ± 0.5 1.000 17.4 ± 1.1 0.3 ± 0.4 1.000 JTT-total 32.8 ± 5.0 43.1 ± 5.9 10.3 ± 2.7 0.004 43.7 ± 6.1 10.9 ± 2.7 0.003 22.9 ± 5.1 26.4 ± 5.8 3.5 ± 1.4 0.097 26.6 ± 5.9 3.8 ± 1.6 0.152 JTT-gross 14.5 ± 2.4 19.0 ± 2.8 4.5 ± 1.1 0.003 19.3 ± 2.9 4.8 ± 1.2 0.003 10.9 ± 2.5 12.0 ± 2.8 1.2 ± 0.8 0.863 12.7 ± 2.9 1.3 ± 0.9 0.902 JTT-fine 18.3 ± 2.7 24.1 ± 3.2 5.8 ± 1.6 0.008 24.4 ± 3.3 6.2 ± 1.7 0.009 12.0 ± 2.7 14.4 ± 3.1 2.5 ± 1.1 0.158 15.2 ± 3.2 2.7 ± 1.2 0.193 Abbreviations: SG Smart Glove, CON conventional intervention, FM Fugl–Meyer assessment, JTT Jebsen–Taylor hand function test Values are presented as mean ± standard deviation Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 7 of 10 Fig. 4 Mean and standard errors for the JTT scores in the SG and Fig. 3 Mean and standard errors for the FM scores in the SG and CON groups. Abbreviations: JTT, Jebsen–Taylor hand function test; CON groups. Abbreviations: FM, Fugl–Meyer assessment, SG, Smart SG, Smart Glove; CON, conventional intervention Glove; CON, conventional intervention composite SIS score (F = 5.76, df = 1.0, P = 0.021) and standard OT than using amount-matched conventional re- the overall SIS score (F = 6.408, df = 1.0, P = 0.015). habilitation, without any adverse events, in stroke survivors. Moreover, among individual domain scores, the Time × Additionally, this study noted improvements in the SIS- Group interactions were significant for the mobility score ADLs/IADLs score beyond the minimum clinically im- (F = 5.333, df = 1.0, P = 0.026) and the social participation portantdifference(MCID) of5.9 in theSGgroup [23]. score (F = 5.858, df = 1.0, P =0.020). The improvements in the FMA and JTT scores in the SG group were maintained at the 1-month follow-up. Discussion A previous systematic review found that task-specific The present study noted greater improvements in multiple training enhanced arm function; however, this review outcomes of the distal upper extremity, including motor failed to show the beneficial effects of the intervention on impairment (FM-total, FM-prox, and FM-dist scores), hand hand function [24]. Additionally, a recent systematic re- functions (JTT-total and JTT-gross scores), and HRQoL view failed to show the beneficial effects of VR-based re- (composite SIS, overall SIS, SIS-social participation, and habilitation on distal upper extremity function in stroke SIS-mobility scores) using VR-based rehabilitation with survivors [9]. However, our study found that the functional Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 8 of 10 Table 3 Baseline and Post-intervention SIS Scores in the SG and CON Groups T0 T2 Repeated-measures ANOVA Outcome variables SG CON SG CON F P-value Strength 33.5 ± 19.9 25.9 ± 4.8 37.0 ± 4.0 29.2 ± 3.9 0.008 0.929 Hand function 45.9 ± 34.2 42.6 ± 6.1 58.5 ± 31.1 42.4 ± 7.0 2.931 0.094 Mobility 68.6 ± 5.4 76.6 ± 5.5 80.0 ± 3.7 75.7 ± 4.6 5.333 0.026 ADLs/IADLs 61.4 ± 18.5 64.2 ± 5.2 74.0 ± 3.3 68.6 ± 4.4 3.534 0.067 Memory and thinking 73.7 ± 4.9 81.1 ± 5.1 73.4 ± 4.0 80.1 ± 5.6 0.167 0.685 Communication 79.4 ± 24.6 84.5 ± 4.5 82.0 ± 24.4 84.2 ± 4.6 2.702 0.108 Emotion 62.4 ± 13.4 64.4 ± 4.1 64.4 ± 16.7 59.4 ± 3.4 3.669 0.062 Social participation 40.4 ± 20.2 46.4 ± 5.8 49.1 ± 21.5 44.2 ± 3.7 5.858 0.020 Composite SIS 147.7 ± 4.1 153.2 ± 14.5 181.6 ± 59.8 155.2 ± 13.3 5.763 0.021 Overall SIS 465.2 ± 121.5 485.8 ± 31.3 518.3 ± 100.2 483.7 ± 28.7 6.408 0.015 Abbreviations: SG Smart Glove, CON conventional intervention, ADLs/IADLs activities of daily living/instrumental activities of daily living, SIS Stroke Impact Scale Values are presented as mean ± standard deviation improvements of the distal upper extremity were better effects of VR-based rehabilitation without the use of add- using VR-based rehabilitation than using conventional itional tools. rehabilitation, according to the FMA-dist and JTT-total We found that VR-based rehabilitation had beneficial ef- scores. Furthermore, the functional improvements of the fects on both the proximal and distal upper extremity, distal upper extremity using VR-based rehabilitation were which were indicated by the FMA-prox and FMA-dist more definite for gross hand function than for fine hand scores, respectively. These results were not expected, as we function, as a significant difference was noted in the JTT- believed that the VR-based rehabilitation would only influ- gross score but not in the JTT-fine and PPT scores. There- ence the distal upper extremity because the SG system fore, the improvements in distal upper extremity function focuses on the distal upper extremity. A possible explan- using VR-based rehabilitation might have resulted from ation for the results is that the distal part plays a major role the task-specificity of the SG system, as the intervention in upper extremity function as an end-effector; therefore, mainly consisted of gross movements of the distal upper the high activity of the distal part during rehabilitation pro- extremity without fine movements involving individual moted the active use of the affected upper extremity, which fingers. The following are the highlights of task-specific was neglected or not used, thus overcoming learned non- training: relevance to the patient and context, randomly use [3]. Training using the SG system allowed the perform- ordered practice sequence, repetition, reconstruction of ance improvement to be generalized to untrained tasks. the task, and positive reinforcement [25]. The SG system Recent studies have shown that the effects of VR-based includes all the abovementioned properties of task-specific rehabilitation for the upper extremity were transferred to training. The games in the SG system require participants distinct tasks in stroke survivors [10, 13]. Moreover, this to repeat the reconstructed tasks mimicking ADLs, which extension of performance improvement to untrained tasks are relevant to them and the context. Therapists could after task-specific training was not dependent on the prepare specific intervention schedules by combining similarity between tasks [26]. Krakauer advocated that a games; thus, a randomly ordered practice sequence could rehabilitation technique should allow the extension of be prepared. In addition, the artificial intelligence of the performance improvement to untrained tasks [27]. SG system can adjust the difficulty of tasks according to Therefore, we believe that the SG system is an ideal re- participant performance; thus, allowing the completion of habilitation tool. the task. This provides a feeling of achievement, which is We noted greater improvements in the composite SIS, enhanced by audio or visual feedback in the game, leading overall SIS, and SIS-social participation, and SIS-mobility to positive reinforcement. Therefore, the task-specific scores using VR-based rehabilitation than using conven- training effects might be maximized using the SG system. tional rehabilitation. These findings are largely consistent A recent study showed that the improvement in distal with those of previous randomized controlled trials that upper limb function was greater using VR-based rehabili- showed greater improvements in overall SIS scores or tation with an actuated glove than using conventional re- some physical domain scores using constraint-induced habilitation, according to the JTT scores [13]. In contrast, movement therapy (CIMT) than conventional therapy the SG system used in our study did not include an actu- [28, 29]. However, a previous study on CIMT reported im- ated apparatus; thus, our results represent the task-specific provements in only SIS-hand function scores [28]. A Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 9 of 10 Cochrane review on VR commented on the low number with the SIS; thus, the long-term beneficial effects of of studies regarding participation restriction or QoL [9]. rehabilitation using the SG system on HRQoL could Additionally, a recent systematic review suggested the per- not be determined. Fifth, we used a new scoring system formance of more studies evaluating the effects of upper for the JTT instead of raw time; thus, comparisons with limb interventions on HRQoL [30]. A recent study, which other results or broader interpretation might be limited. was not included in these reviews, showed the possible Sixth, participants who exhibited hand flaccidity were benefits of VR-based rehabilitation on HRQoL by compar- excluded, as the SG system does not provide assistive ing Short-Form Health Survey scores between VR-based re- force. We are performing another clinical trial with a habilitation and conventional rehabilitation [31]. One item combination of functional electrical stimulation and the of the Short-Form Health Survey (role limitation due to SG system to overcome this limitation. physical problem) showed greater improvement after VR- based rehabilitation than after conventional rehabilitation. Conclusions Our study also showed the beneficial effects of VR-based VR-based rehabilitation combined with standard OT rehabilitation on HRQoL, including more generalized ef- might be more effective than amount-matched conven- fects on HRQoL, which are represented by improvements tional rehabilitation for improving distal upper extremity in the overall and composite SIS scores in accordance with function and HRQoL in stroke survivors. Therefore, the our functional results. SG system used in VR-based rehabilitation might be an The present study had several limitations. First, the im- ideal rehabilitation tool for the distal upper extremity in provements in the FM scores did not exceed the MCID of stroke survivors. 6.6 points [32]. Additionally, the improvements in the JTT Abbreviations and PPT scores did not have established MCID values. ADLs: activities of daily living; CIMT: constraint-induced movement therapy; Therefore, it is not appropriate to state that the improve- CON: conventional intervention; FM: Fugl–Meyer assessment; HRQoL: health- related quality of life; JTT: Jebsen–Taylor hand function test; MCID: minimum ments in the SG group were within the minimum values clinically important difference; OT: occupational therapy; PPT: Purdue required to consider the intervention clinically important. pegboard test; QoL: quality of life; SG: Smart Glove; SIS: Stroke Impact Scale; However, considering the findings of previous studies on VR: virtual reality. VR (FM MCIDs between 3.5 and 4.5) [9, 33], the improve- Competing interests ments in the FM scores were good in the SG group. Joon-Ho Shin received support for application of the Smart Glove system from Therefore, the SG system might be a clinically meaningful Neofect during the performance of the study. Younggeun Choi is an inventor VR-based rehabilitation tool. Moreover, the improvement of the Smart Glove system and holds the patent for the system and its manufacture. Soobin Lee and Younggeun Choi hold equity positions in in the SIS-ADLs/IADLs score was beyond the MCID of Neofect Inc. and are workers at Neofect. Neofect has a direct financial interest 5.9 in the SG group. Therefore, the SG system can be con- in the results of the study and has conferred or will confer a financial benefit on sidered a clinically useful rehabilitation tool. Furthermore, Soobin Lee and Younggeun Choi. Although the Smart Glove system from Neofect was used in the present study, Neofect was not involved in the study the ceiling effect of the FM score might hamper the obser- conception, data collection, data analysis, and reporting of findings. vation of a further improvement in the FM score. Second, the FM score was used as the primary outcome and for Authors’ contributions JHS and SK conceived the study and prepared the research protocol. SL and power calculation; however, the target of the SG system YC provided the Smart Glove system, and undertook its maintenance and was the distal upper extremity. We used the FM score, as repair. BS provided the games embedded in Smart Glove system. JYL, MYK, there was no appropriate VR-based rehabilitation study and YJJ were involved in clinical management and data collection. JHS and SK performed statistical data analysis. SL and BS prepared the illustrations. JHS, using outcome measures focused on the hand, such as the YJL, MYK, and YJJ interpreted the results. All authors participated in the drafting JTT. In addition, we hoped to investigate the generalized of the manuscript. All authors read and approved the final manuscript. effects of the SG system on the upper extremity by using the FM score. Future studies using outcome measures Acknowledgments The authors would like to thank Jae-Bong Lee for statistical consultation. relevant to the distal upper extremity are needed to exam- This study was supported by the ICT R&D program funded by MSIP/IITP ine the efficacy of the present system. Third, the study (2014-050-005-064, Development of a Collaborative Assistive Smart Rehabilitation did not include a group that received training using Platform based on Big Data). only the SG system or a group that received only stand- Author details ard OT. We provided 30 min of standard OT in the SG 1 National Rehabilitation Center, Ministry of Health and Welfare, Seoul, Korea. 2 3 group from an ethical standpoint because there were Department of Law, Hanyang University, Seoul, Korea. Neofect, Yong-in, 4 5 Korea. School of Games, Hongik University, Seoul, Korea. Department of no clinical data to support the use of the SG system. Applied Computer Engineering, Dankook University, Yong-in, Korea. Thus, it is difficult to state that the good outcomes in 6 Department of Rehabilitation Medicine, National Rehabilitation Center, theSGgroup resulted fromtheuse of theSGsystem. Ministry of Health and Welfare, Samgaksan-ro 58, Gangbuk-gu, Seoul 142-884, Korea. A future study is warranted to compare rehabilitation using the SG system only with conventional rehabilita- Received: 26 October 2015 Accepted: 12 February 2016 tion. Fourth, follow-up evaluations were not performed Shin et al. 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A systematic review of repetitive functional task practice with modelling of resource use, costs Submit your manuscript at and effectiveness. Health Technol Assess. 2008;12(30):140. www.biomedcentral.com/submit http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of NeuroEngineering and Rehabilitation Springer Journals

Effects of virtual reality-based rehabilitation on distal upper extremity function and health-related quality of life: a single-blinded, randomized controlled trial

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Springer Journals
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Copyright © 2016 by Shin et al.
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Biomedicine; Neurosciences; Neurology; Rehabilitation Medicine; Biomedical Engineering
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10.1186/s12984-016-0125-x
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26911438
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Abstract

Background: Virtual reality (VR)-based rehabilitation has been reported to have beneficial effects on upper extremity function in stroke survivors; however, there is limited information about its effects on distal upper extremity function and health-related quality of life (HRQoL). The purpose of the present study was to examine the effects of VR-based rehabilitation combined with standard occupational therapy on distal upper extremity function and HRQoL, and compare the findings to those of amount-matched conventional rehabilitation in stroke survivors. Methods: The present study was a single-blinded, randomized controlled trial. The study included 46 stroke survivors who were randomized to a Smart Glove (SG) group or a conventional intervention (CON) group. In both groups, the interventions were targeted to the distal upper extremity and standard occupational therapy was administered. The primary outcome was the change in the Fugl–Meyer assessment (FM) scores, and the secondary outcomes were the changes in the Jebsen–Taylor hand function test (JTT), Purdue pegboard test, and Stroke Impact Scale (SIS) version 3.0 scores. The outcomes were assessed before the intervention, in the middle of the intervention, immediately after the intervention, and 1 month after the intervention. Results: The improvements in the FM (FM-total, FM-prox, and FM-dist), JTT (JTT-total and JTT-gross), and SIS (composite and overall SIS, SIS-social participation, and SIS-mobility) scores were significantly greater in the SG group than in the CON group. Conclusions: VR-based rehabilitation combined with standard occupational therapy might be more effective than amount-matched conventional rehabilitation for improving distal upper extremity function and HRQoL. Trial registration: This study is registered under the title “Effects of Novel Game Rehabilitation System on Upper Extremity Function of Patients With Stroke” and can be located in https://clinicaltrials.gov with the study identifier NCT02029651. Keywords: Rehabilitation, Upper extremity, Virtual reality therapy, Quality of life, Video games * Correspondence: [email protected] National Rehabilitation Center, Ministry of Health and Welfare, Seoul, Korea Department of Rehabilitation Medicine, National Rehabilitation Center, Ministry of Health and Welfare, Samgaksan-ro 58, Gangbuk-gu, Seoul 142-884, Korea Full list of author information is available at the end of the article © 2016 Shin et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 2 of 10 Background Methods Regaining upper extremity function is one of the Study design major goals in stroke survivors, as it is important for The present study was a single-blinded, randomized con- performing activities of daily living (ADLs). However, trolled trial performed at National Rehabilitation Center, approximately 80 % of stroke survivors have upper ex- an urban rehabilitation hospital in Seoul, Korea. Eligible tremity limitations, and these limitations persist in ap- participants were randomly assigned to a Smart Glove proximately half of these survivors in the chronic (SG) or conventional intervention (CON) group using a phase [1, 2]. Distal upper extremity function is vital computer-generated randomized scheme. The allocation for performing ADLs, such as holding objects like was performed using sealed opaque envelopes with the utensils, turning a doorknob or key in a lock, tele- group name, which were placed in a plastic container in phone or computer use, and writing, and is strongly numerical order. Randomization, outcome measurements, related to quality of life (QoL) in stroke survivors [3]. and data analysis were performed by different individuals In stroke survivors, the distal upper extremity is se- who were not involved in the intervention. This study was verely affected and is the last body part to recover [4]. registered at clinicaltrials.gov (NCT02029651) and was ap- Therefore, improving distal upper extremity function proved by the Ethics Committee of the National Rehabili- is of primary importance in the rehabilitation of stroke tation Center, Korea. All participants provided informed survivors. written consent before enrollment. Recent studies have emphasized the use of interven- tions that are focused and repetitive, relevant to real-life, Participants and actively performed in order to promote cortical The study included 46 consecutive participants with upper reorganization and neuroplasticity [5–8]. In this context, extremity functional deficits caused by stroke, who were conventional interventions have been complemented by present in a rehabilitation hospital. The inclusion criteria novel technologies such as virtual reality (VR). were as follows: (1) first-ever ischemic or hemorrhagic VR-based rehabilitation is promising in stroke survi- stroke; (2) complaints of unilateral upper extremity func- vors, and many types of VR-based rehabilitation ap- tional deficits after stroke; and (3) presence of a score of at paratus from commercial video game equipment to least 2 points on the medical research council scale robotics are currently being developed and used. In [14] for wrist flexion/extension or forearm pronation/ the area of upper limb rehabilitation, a large number supination, as the SG system can be operated only with of studies have been performed in stroke survivors, volitional movements and does not involve external as- and a recent systematic review concluded that the use sistance. The exclusion criteria were as follows: (1) age of VR-based rehabilitation is superior to amount- <18 years; (2) uncontrolled hypertension, unstable an- matched conventional rehabilitation for improving gina, recent myocardial infarction, or any history of upper limb function [9]. Nevertheless, most studies on seizure; (3) predisposing psychological disorders that VR-based rehabilitation for the upper extremity re- could impede participation; (4) neurological disorders ported on the proximal upper extremity, with limited that cause motor deficits, such as Parkinson’sdisease information on the distal upper extremity. Although 2 and peripheral neuropathy; (5) severe aphasia resulting previous studies showed promising results regarding in communication difficulties that could influence the VR-based rehabilitation for the distal upper extremity, intervention and outcome measures; (6) cognitive im- these studies did not include a control group [10, 11]. pairment resulting in cooperation difficulties (a score of Randomized control trials have been performed using ≤24 in the Mini-Mental State Examination) [15]; and a VR system with different types of gloves; however, a (7) severe pain impeding upper extremity rehabilitation definite conclusion about the treatment effect could (numeric pain rating scale score ≥ 7) [16]. not be obtained owing to the low number of partici- pants [12, 13]. Furthermore, the effects of VR-based Intervention rehabilitation on health related quality of life (HRQoL) All participants received a 4-week face-to-face interven- have not been appropriately assessed, although the tion program (SG or CON) individually (20 sessions for QoL of stroke survivors is crucial for comprehensive 30 min per day) in a room for the intervention, as well rehabilitation. as standard OT daily for 30 min in a room for OT. The Therefore, the objective of the present study was to intervention programs exclusively focused on the distal examine the effects of VR-based rehabilitation com- upper extremity and were administered by 3 trained oc- bined with standard occupational therapy (OT) on dis- cupational therapists who were involved in both the in- tal upper extremity function and HRQoL, and compare terventions and were exclusively dedicated to this study. the findings to those of amount-matched conventional The therapists were sequentially allocated such that the rehabilitation in stroke survivors. intervention to be performed by each therapist was Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 3 of 10 automatically selected based on the randomized alloca- scores. The games simulate ADLs, such as catching tion of the SG and CON groups in order to minimize butterflies or balls, squeezing oranges, fishing, cooking, therapist bias. The intervention time was the same in cleaning the floor, pouring wine, painting fences, and both the groups. Standard OT involved range of motion turning over pages, which allows the participants to and strengthening exercises for the affected limb, table- easily familiarize themselves with the training program top activities, and training for ADLs and was adminis- and motivates them to perform the tasks. tered by occupational therapists who were not involved The intervention in the SG group involved the above- in this study. mentioned categories of movements of the distal upper extremity in order to achieve goals in a specific task Smart glove intervention based on visual feedback in real time. In addition, the The RAPAEL Smart Glove™ (Neofect, Yong-in, Korea) is a difficulty of the intervention was adjusted by the artifi- biofeedback system designed for distal upper extremity cial intelligence of the system according to participant rehabilitation in stroke survivors (Fig. 1). It includes a performance [17]. The function for the algorithm is glove-shaped sensor device and a software application. given by The sensor device tracks the motion and posture of the wearer’s distal limb and recognizes functional movements, DL ¼ DL  1 þ α P −P ð1Þ i i−1 i−1 ref such as forearm pronation/supination, wrist flexion/exten- sion, radial-ulnar deviation, and finger flexion/extension. where DL is the difficulty level for the current trial i, α is An inertial measurement unit sensor in the device mea- aconstant for therateofupdate, P is the performance t-1 sures the 3-dimensional orientation of the distal limb, and on the previous trial, and P is the reference perform- ref 5 bending sensors estimate the degree of bending of the ance. In the games, the performance in the algorithm is fingers. The gathered sensing data is transmitted and re- mostly range of motion for each function movement, but ceived via wireless communication systems such as Blue- it could be other quantity such as time depending on the tooth. The software application manipulates virtual hands games. The reference performance is set to be 80 % of the or virtual objects in training games according to the re- active range of motion or 80 % of the maximum perform- ceived data. In addition, this system can evaluate the active ance from previous trials. The difficulty level could be and passive range of motion for each functional movement. position of target, target performance, duration, move- The training games in the SG system are categorized ac- ment speed, or others depending on the game. The algo- cording to the intended movements as follows: forearm rithm progressively increases the difficulty level until the pronation/supination, wrist flexion/extension in the verti- current performance is below the reference performance, cal plane, wrist flexion/extension in the horizontal plane and it keeps modulating the difficulty level to make the with gravity eliminated, wrist radial/ulnar deviation in the performance stay near the reference performance. vertical plane, wrist radial/ulnar deviation in the horizon- tal plane with gravity eliminated, finger flexion/extension, Conventional intervention and complex movements. In each game, the wearer is The intervention in the CON group involved the same required to successfully perform a task that is related to categories of movements of the distal upper extremity as the specific intended movement in order to obtain high those in the SG group in order to minimize confounding Fig. 1 The RAPAEL Smart Glove™ system and the task-specific games of this system Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 4 of 10 between the 2 groups. Therefore, all factors, except hand (PPT-aff), both hands (PPT-both), and assembly the use of the SG system, were consistent between the (PPT-assembly). 2groups. Thedifficultyofthe interventionwasad- HRQoL was measured using a stroke-specific, self- justed by occupational therapists according to partici- reported patient-perspective assessment tool, the Stroke pant performance. Impact Scale (SIS) version 3.0, which consists of the following 8 domains: strength, hand function, mobility, physical and instrumental activities of daily living (ADLs/ Outcome measures IADLs), memory and thinking, communication, emotion, The baseline characteristics assessed were age, sex, hand- and social participation [20]. The score for each domain edness, time since stroke onset, stroke type, affected body ranges from 0 to 100, with higher scores indicating better side, and the medical research council scale scores of the HRQoL. The hand function, ADLs/IADLs, and social par- flexor/extensor of the shoulder, elbow, and wrist. ticipation scores were combined into a composite SIS score to demonstrate the comprehensive impact of func- Primary outcome tional change relevant to the interventions used in the Motor impairment of the affected upper limb was evalu- present study from the perspective of the international ated using the upper extremity Fugl–Meyer assessment classification of functioning, disability, and health [21]. (FM-total; 33 items with a 3-point ordinal scale; range, Additionally, the overall SIS score was calculated as the 0–66), with higher scores indicating lower impairment sum of all domain scores. The secondary outcomes were [18]. We further divided the FM-total score into prox- the changes in the JTT, PPT, and SIS scores. imal (shoulder, elbow, and forearm; FM-prox) and distal The FM, JTT, and PPT scores were determined before (wrist and hand; FM-dist) scores. The primary outcome the intervention (T0), in the middle of the intervention was the change in the FM scores. (after the 10th session; T1), immediately after the inter- vention (T2), and 1 month after the intervention (T3). Secondary outcomes The SIS scores were determined only at T0 and T2. A Hand function was evaluated using the Jebsen–Taylor trained and blinded outcome assessor who was unaware hand function test (JTT) and Purdue pegboard test (PPT). of group allocation performed all outcome measure- The JTT was used to assess hand function mimicking ments. Adverse events were recorded during the inter- ADLs. It involves a series of 7 timed subtests, including vention and at outcome measurements. writing, simulated page turning, picking up small objects, simulated feeding, stacking checkers, picking up large Sample size light objects, and picking up large heavy objects. Quantifi- As this was the first study to assess the efficacy of the SG cation is not possible if a subtest cannot be completed system in people with stroke, power calculation was per- within a certain time, as the result is a continuous time formed using FM scores from a previous study, which variable, and a subtest is considered to have a missing applied VR-based rehabilitation for the upper extremity in value if it cannot be completed. Therefore, we used a scor- stroke survivors, hypothesizing a similar efficacy between ing system (each subtest score ranges from 0 to 15, and our rehabilitation and the previous rehabilitation [22]. Ac- the total score calculated as the sum of each subtest score cordingly, 18 participants were required in each group to ranges from 0 to 105), which has been shown to have provide 80 % power for efficacy evaluation, setting the α good validity in people with stroke [19]. We used the total level at 0.05. Finally, we calculated that 46 participants score (JTT-total), and divided the JTT-total into gross were needed, considering a 20 % dropout rate. (stacking checkers, picking up large light objects, and picking up large heavy objects; JTT-gross) and fine hand Statistical analysis function (writing, simulated page turning, picking up An intention-to-treat analysis was performed, which in- small objects, and simulated feeding; JTT-fine) scores. cluded all participants who were enrolled in the present The PPT was used to evaluate fine hand motor profi- study regardless of intervention completion. We used the ciency. It involves a board with 2 parallel rows having 25 last observed outcome values for the determination of holes each. The participants are required to pick and missing values in dropouts, conservatively assuming that place pins into the holes, and the score is the number of no changes occurred after the last observation. At base- pins placed in 30 s. Scores are assessed for the right line, the mean values of variables were compared between hand, left hand, and both hands, and the sum of these the SG and CON groups using the Mann–Whitney U test scores is determined. The test involves 4 trials. Add- and Fisher exact test for continuous and categorical vari- itionally, scores are assessed for the number of assem- ables, respectively. Analysis of variance was performed for bled pins, washers, and collars in 60 s. We modified repeated measurements in the groups (SG and CON the original PPT, and recorded scores for the affected groups) as the between-patient factors and time (T0, T1, Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 5 of 10 T2, and T3) as the within-patient factor in order to there were no differences in the demographics and clinical compare the effects of each intervention on the FMA, characteristics between the SG and CON groups (Table 1). JTT, and PPT scores. The main effects of Group, Time, and Time × Group interactions were evaluated. The Primary outcomes Greenhouse-Geisser procedure was applied when the The FM scores of the SG and CON groups are presented assumption of sphericity was violated, and the post-hoc in Table 2. There were no differences in the FM-total, test was performed. All statistical analyses were performed FM-prox, and FM-dist scores between the 2 groups at T0. using SPSS software (version 17.0; IBM, Armonk, NY), There were significant improvements in the FM-total, and a P-value <0.05 was considered statistically significant. FM-prox, and FM-dist scores in the SG group during the intervention and at the follow-up; however, no significant changes were noted in the CON group (Fig. 3). The im- Results provements in the SG group were supported by significant Of the 46 participants included in the present study, 33 Time × Group interactions (FM-total: F = 6.48, df = 1.46, completed the 4-week intervention programs and assess- P = 0.006; FM-prox: F = 5.73, df = 1.705, P =0.007; FM- ments at T2 and 23 completed the follow-up assessments dist: F = 4.64, df = 1.38, P =0.024). at T3. During the study, 5 and 8 participants from the SG and CON groups, respectively, did not complete the inter- Secondary outcomes vention programs. The sample sizes at the assessment time Jebsen–Taylor hand function test points are presented in Fig. 2. There were no serious ad- The JTT scores of the SG and CON groups are presented verse events, and only 1 participant from the CON group in Table 2. There were no significant differences in the dropped out owing to dizziness, which was unrelated to JTT-total, JTT-gross, and JTT-fine scores between the 2 the intervention. Thus, most of the study withdrawals were groups at T0. The post-hoc test found that there were sig- related to uncooperativeness, and the number was higher nificant improvements in the JTT-total, JTT-gross, and than that hypothesized in the study design. At baseline, JTT-fine scores in the SG group during the intervention Fig. 2 Flowchart of the participants through the study. Abbreviations: SG, Smart Glove; CON, conventional intervention Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 6 of 10 Table 1 Participant Characteristics SG group (n = 24) CON group (n = 22) P-value Demographics Age, years 57.2 ± 10.3 59.8 ± 13.0 0.373 Gender, male 19 (79.2) 17 (77.3) 0.578 Dominant hand, right 23 (95.8) 22 (100) 0.522 Stroke characteristics Time from stroke, months 13.6 ± 13.4 15.0 ± 14.6 0.809 Affected arm, right 9 (37.5) 11 (50.0) 0.590 Ischemia 15 (62.5) 14 (63.6) 0.590 Clinical characteristics MRC scale shoulder flexor 3.2 ± 0.7 3.3 ± 0.7 0.738 MRC scale shoulder extensor 3.3 ± 0.6 3.4 ± 0.6 0.703 MRC scale elbow flexor 3.6 ± 0.6 3.8 ± 0.6 0.472 MRC scale elbow extensor 3.5 ± 0.6 3.7 ± 0.6 0.228 MRC scale wrist flexor 3.4 ± 0.6 3.6 ± 0.7 0.490 MRC scale wrist extensor 3.4 ± 0.7 3.5 ± 0.8 0.719 FM-total score 53.4 ± 8.7 48.2 ± 12.3 0.169 Abbreviations: SG Smart Glove, CON conventional intervention, MRC medical research council, FM Fugl–Meyer assessment Values are presented as mean ± standard deviation or number (%). There were no significant differences between groups at baseline for the characteristics Mann–Whitney U test Fisher’s exact test and at the follow-up; however, no significant changes were df = 1.547, P = 0.350), and PPT-assembly (F = 1.934, noted in the CON group (Fig. 4). The improvements in df = 2.265, P =0.288, P = 0.144) were not significant, indi- the JTT-total and JTT-gross scores in the SG group were cating a similar increase in fine hand motor function in supported by significant Time × Group interactions (JTT- both groups. total: F = 4.073, df = 1.497, P = 0.032; JTT-gross: F = 4.155, df = 1.705, P = 0.025). However, the Time × Group inter- Stroke impact scale action for the JTT-fine score was not significant, indicat- There were no significant differences in the composite, ing a similar pattern in both groups (F = 2.207, df = 1.493, overall, and individual SIS domain scores between the 2 P =0.131). groups at T0 (Table 3). The post-hoc test found that the SG group had significant improvements in the com- Perdue pegboard test posite (36.7 ± 10.0, P = 0.001) and overall SIS scores The PPT-aff, PPT-both, and PPT-assembly scores (61.0 ± 19.6, P = 0.005) during the intervention. How- were higher in the SG group than in the CON group ever, no significant improvements in the composite at T0 (P = 0.033, P = 0.018, and P = 0.009, respect- (1.9 ± 10.5, P= 0.856) and overall SIS scores (2.1 ± 15.1, ively). The Time × Group interactions for PPT-aff (F P= 0.889) were noted in the CON group. Additionally, = 1.260, df = 1.912, P = 0.288), PPT-both (F = 1.016, the Time × Group interactions were significant for the Table 2 FM and JTT Scores in the SG and CON Groups SG (n = 24) CON (n = 22) T0 T2 Change P-value T3 Change P-value T0 T2 Change P-value T3 Change P-value (T2 − T0) (T3 − T0) (T2 − T0) (T3 − T10) FM-total 53.4 ± 1.8 58.3 ± 1.7 4.9 ± 1.0 <0.001 58.5 ± 1.7 5.3 ± 1.1 0.001 48.2 ± 2.6 49.6 ± 2.7 1.4 ± 0.8 0.512 49.5 ± 2.7 1.3 ± 0.8 0.592 FM-prox 30.0 ± 1.0 32.5 ± 0.9 2.5 ± 0.6 0.001 32.7 ± 0.9 2.6 ± 0.6 0.001 28.3 ± 1.4 28.9 ± 1.4 0.6 ± 0.4 0.538 29.0 ± 1.4 0.7 ± 0.4 0.471 FM-dist 19.4 ± 0.7 21.2 ± 0.7 1.8 ± 0.5 0.004 21.2 ± 0.7 1.8 ± 0.5 0.007 17.3 ± 1.1 17.4 ± 1.1 0.3 ± 0.5 1.000 17.4 ± 1.1 0.3 ± 0.4 1.000 JTT-total 32.8 ± 5.0 43.1 ± 5.9 10.3 ± 2.7 0.004 43.7 ± 6.1 10.9 ± 2.7 0.003 22.9 ± 5.1 26.4 ± 5.8 3.5 ± 1.4 0.097 26.6 ± 5.9 3.8 ± 1.6 0.152 JTT-gross 14.5 ± 2.4 19.0 ± 2.8 4.5 ± 1.1 0.003 19.3 ± 2.9 4.8 ± 1.2 0.003 10.9 ± 2.5 12.0 ± 2.8 1.2 ± 0.8 0.863 12.7 ± 2.9 1.3 ± 0.9 0.902 JTT-fine 18.3 ± 2.7 24.1 ± 3.2 5.8 ± 1.6 0.008 24.4 ± 3.3 6.2 ± 1.7 0.009 12.0 ± 2.7 14.4 ± 3.1 2.5 ± 1.1 0.158 15.2 ± 3.2 2.7 ± 1.2 0.193 Abbreviations: SG Smart Glove, CON conventional intervention, FM Fugl–Meyer assessment, JTT Jebsen–Taylor hand function test Values are presented as mean ± standard deviation Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 7 of 10 Fig. 4 Mean and standard errors for the JTT scores in the SG and Fig. 3 Mean and standard errors for the FM scores in the SG and CON groups. Abbreviations: JTT, Jebsen–Taylor hand function test; CON groups. Abbreviations: FM, Fugl–Meyer assessment, SG, Smart SG, Smart Glove; CON, conventional intervention Glove; CON, conventional intervention composite SIS score (F = 5.76, df = 1.0, P = 0.021) and standard OT than using amount-matched conventional re- the overall SIS score (F = 6.408, df = 1.0, P = 0.015). habilitation, without any adverse events, in stroke survivors. Moreover, among individual domain scores, the Time × Additionally, this study noted improvements in the SIS- Group interactions were significant for the mobility score ADLs/IADLs score beyond the minimum clinically im- (F = 5.333, df = 1.0, P = 0.026) and the social participation portantdifference(MCID) of5.9 in theSGgroup [23]. score (F = 5.858, df = 1.0, P =0.020). The improvements in the FMA and JTT scores in the SG group were maintained at the 1-month follow-up. Discussion A previous systematic review found that task-specific The present study noted greater improvements in multiple training enhanced arm function; however, this review outcomes of the distal upper extremity, including motor failed to show the beneficial effects of the intervention on impairment (FM-total, FM-prox, and FM-dist scores), hand hand function [24]. Additionally, a recent systematic re- functions (JTT-total and JTT-gross scores), and HRQoL view failed to show the beneficial effects of VR-based re- (composite SIS, overall SIS, SIS-social participation, and habilitation on distal upper extremity function in stroke SIS-mobility scores) using VR-based rehabilitation with survivors [9]. However, our study found that the functional Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 8 of 10 Table 3 Baseline and Post-intervention SIS Scores in the SG and CON Groups T0 T2 Repeated-measures ANOVA Outcome variables SG CON SG CON F P-value Strength 33.5 ± 19.9 25.9 ± 4.8 37.0 ± 4.0 29.2 ± 3.9 0.008 0.929 Hand function 45.9 ± 34.2 42.6 ± 6.1 58.5 ± 31.1 42.4 ± 7.0 2.931 0.094 Mobility 68.6 ± 5.4 76.6 ± 5.5 80.0 ± 3.7 75.7 ± 4.6 5.333 0.026 ADLs/IADLs 61.4 ± 18.5 64.2 ± 5.2 74.0 ± 3.3 68.6 ± 4.4 3.534 0.067 Memory and thinking 73.7 ± 4.9 81.1 ± 5.1 73.4 ± 4.0 80.1 ± 5.6 0.167 0.685 Communication 79.4 ± 24.6 84.5 ± 4.5 82.0 ± 24.4 84.2 ± 4.6 2.702 0.108 Emotion 62.4 ± 13.4 64.4 ± 4.1 64.4 ± 16.7 59.4 ± 3.4 3.669 0.062 Social participation 40.4 ± 20.2 46.4 ± 5.8 49.1 ± 21.5 44.2 ± 3.7 5.858 0.020 Composite SIS 147.7 ± 4.1 153.2 ± 14.5 181.6 ± 59.8 155.2 ± 13.3 5.763 0.021 Overall SIS 465.2 ± 121.5 485.8 ± 31.3 518.3 ± 100.2 483.7 ± 28.7 6.408 0.015 Abbreviations: SG Smart Glove, CON conventional intervention, ADLs/IADLs activities of daily living/instrumental activities of daily living, SIS Stroke Impact Scale Values are presented as mean ± standard deviation improvements of the distal upper extremity were better effects of VR-based rehabilitation without the use of add- using VR-based rehabilitation than using conventional itional tools. rehabilitation, according to the FMA-dist and JTT-total We found that VR-based rehabilitation had beneficial ef- scores. Furthermore, the functional improvements of the fects on both the proximal and distal upper extremity, distal upper extremity using VR-based rehabilitation were which were indicated by the FMA-prox and FMA-dist more definite for gross hand function than for fine hand scores, respectively. These results were not expected, as we function, as a significant difference was noted in the JTT- believed that the VR-based rehabilitation would only influ- gross score but not in the JTT-fine and PPT scores. There- ence the distal upper extremity because the SG system fore, the improvements in distal upper extremity function focuses on the distal upper extremity. A possible explan- using VR-based rehabilitation might have resulted from ation for the results is that the distal part plays a major role the task-specificity of the SG system, as the intervention in upper extremity function as an end-effector; therefore, mainly consisted of gross movements of the distal upper the high activity of the distal part during rehabilitation pro- extremity without fine movements involving individual moted the active use of the affected upper extremity, which fingers. The following are the highlights of task-specific was neglected or not used, thus overcoming learned non- training: relevance to the patient and context, randomly use [3]. Training using the SG system allowed the perform- ordered practice sequence, repetition, reconstruction of ance improvement to be generalized to untrained tasks. the task, and positive reinforcement [25]. The SG system Recent studies have shown that the effects of VR-based includes all the abovementioned properties of task-specific rehabilitation for the upper extremity were transferred to training. The games in the SG system require participants distinct tasks in stroke survivors [10, 13]. Moreover, this to repeat the reconstructed tasks mimicking ADLs, which extension of performance improvement to untrained tasks are relevant to them and the context. Therapists could after task-specific training was not dependent on the prepare specific intervention schedules by combining similarity between tasks [26]. Krakauer advocated that a games; thus, a randomly ordered practice sequence could rehabilitation technique should allow the extension of be prepared. In addition, the artificial intelligence of the performance improvement to untrained tasks [27]. SG system can adjust the difficulty of tasks according to Therefore, we believe that the SG system is an ideal re- participant performance; thus, allowing the completion of habilitation tool. the task. This provides a feeling of achievement, which is We noted greater improvements in the composite SIS, enhanced by audio or visual feedback in the game, leading overall SIS, and SIS-social participation, and SIS-mobility to positive reinforcement. Therefore, the task-specific scores using VR-based rehabilitation than using conven- training effects might be maximized using the SG system. tional rehabilitation. These findings are largely consistent A recent study showed that the improvement in distal with those of previous randomized controlled trials that upper limb function was greater using VR-based rehabili- showed greater improvements in overall SIS scores or tation with an actuated glove than using conventional re- some physical domain scores using constraint-induced habilitation, according to the JTT scores [13]. In contrast, movement therapy (CIMT) than conventional therapy the SG system used in our study did not include an actu- [28, 29]. However, a previous study on CIMT reported im- ated apparatus; thus, our results represent the task-specific provements in only SIS-hand function scores [28]. A Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 9 of 10 Cochrane review on VR commented on the low number with the SIS; thus, the long-term beneficial effects of of studies regarding participation restriction or QoL [9]. rehabilitation using the SG system on HRQoL could Additionally, a recent systematic review suggested the per- not be determined. Fifth, we used a new scoring system formance of more studies evaluating the effects of upper for the JTT instead of raw time; thus, comparisons with limb interventions on HRQoL [30]. A recent study, which other results or broader interpretation might be limited. was not included in these reviews, showed the possible Sixth, participants who exhibited hand flaccidity were benefits of VR-based rehabilitation on HRQoL by compar- excluded, as the SG system does not provide assistive ing Short-Form Health Survey scores between VR-based re- force. We are performing another clinical trial with a habilitation and conventional rehabilitation [31]. One item combination of functional electrical stimulation and the of the Short-Form Health Survey (role limitation due to SG system to overcome this limitation. physical problem) showed greater improvement after VR- based rehabilitation than after conventional rehabilitation. Conclusions Our study also showed the beneficial effects of VR-based VR-based rehabilitation combined with standard OT rehabilitation on HRQoL, including more generalized ef- might be more effective than amount-matched conven- fects on HRQoL, which are represented by improvements tional rehabilitation for improving distal upper extremity in the overall and composite SIS scores in accordance with function and HRQoL in stroke survivors. Therefore, the our functional results. SG system used in VR-based rehabilitation might be an The present study had several limitations. First, the im- ideal rehabilitation tool for the distal upper extremity in provements in the FM scores did not exceed the MCID of stroke survivors. 6.6 points [32]. Additionally, the improvements in the JTT Abbreviations and PPT scores did not have established MCID values. ADLs: activities of daily living; CIMT: constraint-induced movement therapy; Therefore, it is not appropriate to state that the improve- CON: conventional intervention; FM: Fugl–Meyer assessment; HRQoL: health- related quality of life; JTT: Jebsen–Taylor hand function test; MCID: minimum ments in the SG group were within the minimum values clinically important difference; OT: occupational therapy; PPT: Purdue required to consider the intervention clinically important. pegboard test; QoL: quality of life; SG: Smart Glove; SIS: Stroke Impact Scale; However, considering the findings of previous studies on VR: virtual reality. VR (FM MCIDs between 3.5 and 4.5) [9, 33], the improve- Competing interests ments in the FM scores were good in the SG group. Joon-Ho Shin received support for application of the Smart Glove system from Therefore, the SG system might be a clinically meaningful Neofect during the performance of the study. Younggeun Choi is an inventor VR-based rehabilitation tool. Moreover, the improvement of the Smart Glove system and holds the patent for the system and its manufacture. Soobin Lee and Younggeun Choi hold equity positions in in the SIS-ADLs/IADLs score was beyond the MCID of Neofect Inc. and are workers at Neofect. Neofect has a direct financial interest 5.9 in the SG group. Therefore, the SG system can be con- in the results of the study and has conferred or will confer a financial benefit on sidered a clinically useful rehabilitation tool. Furthermore, Soobin Lee and Younggeun Choi. Although the Smart Glove system from Neofect was used in the present study, Neofect was not involved in the study the ceiling effect of the FM score might hamper the obser- conception, data collection, data analysis, and reporting of findings. vation of a further improvement in the FM score. Second, the FM score was used as the primary outcome and for Authors’ contributions JHS and SK conceived the study and prepared the research protocol. SL and power calculation; however, the target of the SG system YC provided the Smart Glove system, and undertook its maintenance and was the distal upper extremity. We used the FM score, as repair. BS provided the games embedded in Smart Glove system. JYL, MYK, there was no appropriate VR-based rehabilitation study and YJJ were involved in clinical management and data collection. JHS and SK performed statistical data analysis. SL and BS prepared the illustrations. JHS, using outcome measures focused on the hand, such as the YJL, MYK, and YJJ interpreted the results. All authors participated in the drafting JTT. In addition, we hoped to investigate the generalized of the manuscript. All authors read and approved the final manuscript. effects of the SG system on the upper extremity by using the FM score. Future studies using outcome measures Acknowledgments The authors would like to thank Jae-Bong Lee for statistical consultation. relevant to the distal upper extremity are needed to exam- This study was supported by the ICT R&D program funded by MSIP/IITP ine the efficacy of the present system. Third, the study (2014-050-005-064, Development of a Collaborative Assistive Smart Rehabilitation did not include a group that received training using Platform based on Big Data). only the SG system or a group that received only stand- Author details ard OT. We provided 30 min of standard OT in the SG 1 National Rehabilitation Center, Ministry of Health and Welfare, Seoul, Korea. 2 3 group from an ethical standpoint because there were Department of Law, Hanyang University, Seoul, Korea. Neofect, Yong-in, 4 5 Korea. School of Games, Hongik University, Seoul, Korea. Department of no clinical data to support the use of the SG system. Applied Computer Engineering, Dankook University, Yong-in, Korea. Thus, it is difficult to state that the good outcomes in 6 Department of Rehabilitation Medicine, National Rehabilitation Center, theSGgroup resulted fromtheuse of theSGsystem. Ministry of Health and Welfare, Samgaksan-ro 58, Gangbuk-gu, Seoul 142-884, Korea. A future study is warranted to compare rehabilitation using the SG system only with conventional rehabilita- Received: 26 October 2015 Accepted: 12 February 2016 tion. Fourth, follow-up evaluations were not performed Shin et al. 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A systematic review of repetitive functional task practice with modelling of resource use, costs Submit your manuscript at and effectiveness. Health Technol Assess. 2008;12(30):140. www.biomedcentral.com/submit

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