Gait training with a wearable curara ® robot during stroke rehabilitation: a randomized parallel-group trial

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We have developed a non-exoskeleton rehabilitation robot, “curara ® ,” and examined its immediate effect in patients with spinocerebellar degeneration and stroke, but its rehabilitative effect has not been clarified. The purpose of this study was to examine the effect of curara ® on gait training in stroke patients. Methods: Forty stroke patients were enrolled in this study. The participants were divided randomly into two groups (groups A and B). The subjects in group A were assigned RAGT with curara ® type 4, whereas those in group B received conventional therapist-assisted gait training. The clinical trial period was 15 days. The 10-m walking time (10mWT), 6-min walking distance (6mWD), timed up and go test, and gait parameters (stride duration and length, standard deviation of stride duration and length, cadence, ratio of the stance/swing phases, minimum/maximum knee joint angle, and minimum/maximum hip joint angle) were measured using a RehaGait ® analyzer. The Berg Balance Scale was evaluated on days 0 and 14. Gait training was performed for 30 ± 5 min per day through days 2–6 and days 8–13 (total, 12 days) in both groups. The improvement rate was calculated as the difference of values between days 14 and 0 divided by the value on day 0. The improvement rates of the 10mWT and 6mWD were set as the main outcomes. Results: The data of 35 participants were analyzed. There was no significant difference in the main outcomes between both groups. As for intragroup changes, gait speed, stride length, stride duration, and cadence were improved significantly between days 0 and 14 in each group. There was no significant difference between the measured joint angle and the left-right angle ratio of symmetry within or between the groups. When assessing the interaction effect between the day of measurement and group, stride duration and cadence were more significantly improved in group A than in group B. Conclusions: The wearable curara ® robot has the potential to improve gait function during stroke rehabilitation. Trial registration : Japan Registry of Clinical Trials (jRCTs032180163). Registered on February 22, 2019; https://jrct.niph.go.jp/en-latest-detail/jRCTs032180163 UMIN Clinical Trials Registry (UMIN000034237). Registered on September 22, 2018; https://center6.umin.ac.jp/cgi-open-bin/icdr/ctr_view.cgi?recptno=R000038939 robot-assisted gait training stroke rehabilitation randomized controlled trial motor learning hemiparesis Background Recently, robot-assisted gait training (RAGT) has been applied widely to individuals with stroke to regain and improve walking ability [ 1 ]. In the 1990s, body weight-supported treadmill training was introduced in the clinical setting [ 2 ]. Currently, rehabilitation robots with different assistive forms for lower limb movements have become popular, e.g., Gait Trainer® and Haptic Walker®, which assist with foot movements, and Lokomat®, which assists with lower limb orthosis on a treadmill. These devices enable the joints of the lower limbs to move in a state close to normal during walking without voluntary efforts from the patient [ 3 – 5 ]. In addition to stationary rehabilitation robots, wearable rehabilitation robots have been developed recently and used widely in gait training, e.g., Hybrid Assistive Limb (HAL®) and ReWALK® [ 6 ]. Generally, wearable rehabilitation robots are smaller and lighter than stationary rehabilitation robots; therefore, a great advantage of these devices is that individuals wearing them can move around freely. This makes it possible for people with a wearable rehabilitation robot to perform training in daily life. Systematic reviews have reported that rehabilitation robots improve balance and ankle spasticity in patients with brain diseases including stroke [ 7 , 8 ]. In a study investigating the rehabilitative effect of HAL®, the degree of walking independence evaluated by the Functional Ambulation Category was significantly improved in the HAL-wearing group compared to the non-wearing group [ 7 – 10 ]. We started clinical research in 2017 for the practical application of curara®, a wearable rehabilitation robot. We have examined the effect of curara® in patients with spinocerebellar degeneration [ 11 , 12 ] and stroke [ 13 ]. We have shown that the use of curara® improves walking speed, stride length, walking rate, and asymmetry in stroke patients [ 13 ], but we have not yet clarified its effect on gait training. Therefore, the purpose of this study was to examine the effect of curara® on gait training in stroke patients. Methods Participants and instrumentation A total of 40 individuals participated in this study. They fulfilled all of the inclusion criteria and did not fulfill any of the exclusion criteria. The inclusion criteria were: (1) cerebrovascular disease presenting with hemiplegia; (2) aged ≥ 20 years; (3) 14–90 days after stroke onset; (4) able to walk ≥10 m independently with or without a walker and/or brace; and (5) Berg Balance Scale (BBS) score ≥ 26. The exclusion criteria were: (1) possible causes for gait disturbance other than cerebrovascular disease; (2) too thin or obese to fit into curara ® ; and (3) any other reasons that were considered to make the subjects ineligible to participate (for example, severe dementia or psychiatric symptoms, severe spasticity or joint contracture of the paralyzed leg, etc.). The participants were divided randomly into two groups (groups A and B). The participants in group A were assigned RAGT with curara ® , whereas those in group B received conventional therapist-assisted gait training. Treatment was randomly assigned at the Data Center of Center for Clinical Research in Shinshu University Hospital. The randomization list has been generated using Viedoc 4 ™ (Pharma Consulting Group, Sweden) that was used as an electronic data capture system for this study. To balance the two treatment arms, dynamic randomization performed between the two treatment arms in a ratio of 1:1 applying the modified algorithm of Pocock and Simon (as implemented in Viedoc). We used a wearable “curara ® type 4” robot in this study, which weighs approximately 5 kg (four actuator units and the control box) and has a non-exoskeletal structure that does not have direct contact with the hip and knee joints. The basic mechanisms of curara ® are characterized by a torque-sensing technique and synchronized-based control system. Detailed information regarding curara ® is described in our previous reports [11, 13]. Measurements The study period was 15 days in total. We evaluated the participants on days 0, 7, and 14. On these days, they were instructed to walk 10 m on a flat floor at a comfortable speed 9 times while wearing a RehaGait ® analyzer (HASOMED, Magdeburg, Germany). We measured the 10-m walking time (10mWT) with a stopwatch. We collected the following gait parameters using RehaGait ® : stride duration and length, standard deviation of stride duration and length, cadence, ratio of the stance/swing phases, minimum/maximum knee joint angle, and minimum/maximum hip joint angle. We also measured the 6-min walking distance (6mWD) and timed up and go (TUG) test on days 0, 7, and 14. We evaluated the BBS on days 0 and 14. We set the improvement rates of the 10mWT and 6mWD as the main outcome measures, which were calculated as the difference of values between days 14 and 0 divided by the value on day 0. All of the measurements shown above were acquired without wearing curara ® . Rehabilitation program Gait training consisted of a 30 ± 5 min session each day through days 2–6 and days 8–13 (total, 12 days) for both groups. One or two physical therapists accompanied each participant during gait training. For group A, the therapists operated curara ® and prevented falls, but they did not give any advice on gait to the participants. The participants also received a combination of physical (except gait training), occupational, or speech therapy rehabilitation. The maximum rehabilitation time including gait training with curara ® was 3 h/day. We set synchronization gain, gait cycle, and joint angles as the assist conditions of curara ® . Among these, synchronization gain was fixed to 0.1 at the hip joint and 0.3 at the knee joint throughout the rehabilitation period in all participants. The gait cycle and joint angles varied from individual to individual, and they were set according to the gait parameters of the fastest gait performance on days 0 and 7. The amplitude of the joint angle was set at 140% at the unaffected hip joint and 110% at the unaffected knee joint, and the gait cycle was set at 85%. Therefore, the assist conditions were set 40% wider hip joint, 10% wider at the knee joint, and 15% faster in the gait cycle than the gait parameters of the fastest gait performance. The conditions set on day 0 were used for gait training on days 1–6, and those updated on day 7 were utilized on days 8–13. These parameters meant that the amount of assistance provided by the robot was larger at the hip joint than at the knee joint, i.e., the device-in-charge robotic support was more influential at the hip joint than at the knee joint. With these assist conditions, curara ® enabled the participants to reproduce their best gait performance faithfully during gait training. Statistical analysis The distribution of characteristics of the participants between two groups was analyzed by a t -test for continuous variables and a chi-square test for categorical data. The differences of the BBS score and TUG test between days 0 and 14 were analyzed by a paired t -test. The differences of the gait parameters obtained with RehaGait ® were analyzed using a generalized linear mixed model with Bonferroni’s correction. In the model, the day of measurement, group, and the interaction between those two factors were set as the fixed effects, and subject factors and the number of measurements on the same day of measurement were set as random effects. All statistical analyses were performed using IBM SPSS Statistics 24 for Windows. The level of significance was set at p < 0.05 in all tests. Results Of the 40 participants, three in group A and one in group B dropped out of the trial; two participants in group A retracted informed consent because of mental health issues and one discontinued the trial due to robot-induced skin problems, while one participant in group B had a second stroke during the trial period. A total of 36 participants (17 in group A and 19 in group B) completed the program without any negative events. Detailed information on the participants is shown in Table 1 . However, one participant in group B was excluded from the analysis due to extreme outliers in most of the measured items; therefore, the data of 35 participants were analyzed. Table 1 Characteristics of the participants. Group A ( n = 17) mean ± SD Group B ( n = 18) mean ± SD p -value Age (years) 65.1 ± 12.9 63.0 ± 12.9 0.631 Height (cm) 162.2 ± 8.8 166.3 ± 10.0 0.204 Weight (kg) 62.2 ± 10.1 66.5 ± 14.0 0.302 Lower limb length (cm) 77.3 ± 5.5 79.2 ± 6.0 0.327 Brunnstrom Recovery Stage # III-VI IV-VI 0.916 FIM score on day 0 74.8 ± 12.6 75.6 ± 10.2 0.829 BBS on day 0 52.1 ± 4.3 49.1 ± 6.8 0.071 BBS: Berg Balance Scale; FIM: Functional Independence Measure; SD: standard deviation # Brunnstrom Recovery Stage for lower legs The results of the main outcome measures are shown in Table 2 . The mean improvement rates of the 10mWT were 20.6% in group A and 13.9% in group B. However, the difference between both groups was not statistically significant ( p = 0.099). The mean improvement rates of the 6mWD were 16.8% in group A and 19.4% in group B, again with no significant difference between both groups ( p = 0.067). There amount of change in the BBS or TUG was not statistically significant between groups A and B. Table 2 Results of the main outcomes, BBS, and TUG Group A ( n = 17) mean ± SD Group B ( n = 18) mean ± SD p -value Improvement rate 10mWT (%) 20.6 ± 11.6 13.9 ± 11.7 0.099 6mWD (%) 16.8 ± 18.0 19.4 ± 18.5 0.677 Amount of change BBS (score) 1.3 ± 1.4 2.6 ± 2.7 0.087 TUG (s) -1.4 ± 2.0 -1.3 ± 1.6 0.854 10mWT: 10-m walking time; 6mWD: 6-min walking distance; BBS: Berg Balance Scale; SD: standard deviation; TUG: timed up and go The values of the gait parameters obtained by RehaGait® are shown in Table 3 . Almost all of the gait parameters, except maximum flexion angles of the knee joints, improved on day 14 in each group. When examining the interaction effect between the day of measurement and group, stride duration ( p = 0.006) and cadence ( p = 0.012) were more significantly improved in group A than in group B. These results were expected to be reflected in gait speed, and the interaction effect of gait speed was very close to the level of statistical significance ( p = 0.055). Table 3 Gait parameters obtained with RehaGait® Group A ( n = 17) Group B ( n = 18) p -value day 0 day 14 day 0 day 14 Intragroup difference # Interaction effect * Group A Group B Stride duration (s) 1.19 ± 0.17 1.04 ± 0.12 1.15 ± 0.15 1.09 ± 0.19 < 0.001 0.007 0.006 Stride length (m) 1.07 ± 0.20 1.18 ± 0.22 0.99 ± 0.23 1.08 ± 0.23 < 0.001 < 0.001 0.359 Gait speed (m/s) 0.93 ± 0.26 1.17 ± 0.31 0.88 ± 0.28 1.03 ± 0.32 < 0.001 < 0.001 0.055 Cadence (steps/min) 103.1 ± 14.2 116.6 ± 13.1 105.9 ± 14.4 112.6 ± 17.1 < 0.001 < 0.001 0.012 Ratio of the unaffected standing phase (%) 64.5 ± 3.6 62.8 ± 4.0 63.8 ± 4.0 62.9 ± 3.5 0.004 0.077 0.254 Ratio of the affected standing phase (%) 66.5 ± 5.0 64.0 ± 3.9 67.0 ± 4.3 65.4 ± 4.3 < 0.001 < 0.001 0.157 Maximum flexion angles unaffected knee joint (°) 55.2 ± 11.4 56.4 ± 9.9 45.6 ± 13.7 47.7 ± 14.8 0.695 0.235 0.449 affected knee joint (°) 60.1 ± 7.7 60.6 ± 6.7 53.3 ± 7.4 54.8 ± 7.4 1.000 0.734 0.799 unaffected hip joint (°) 6.9 ± 4.9 9.4 ± 4.8 5.4 ± 3.6 6.9 ± 3.9 < 0.001 0.012 0.376 affected hip joint (°) 7.5 ± 4.5 10.2 ± 4.8 6.2 ± 3.9 7.5 ± 3.1 < 0.001 0.085 0.127 Symmetry § 2.5 ± 5.1 1.3 ± 1.1 1.6 ± 1.7 1.9 ± 2.9 0.271 1.000 0.325 # Intragroup difference between days 0 and 14. *Interaction effect: between the day of measurement and group. § Symmetry: ratio of the maximum flexion angles of the affected hip joint to the unaffected hip joint. The index of symmetry was expressed as the ratio of the maximum hip flexion angle of the affected leg to that of the unaffected leg in each group (Table 3 ). However, there was no significant difference in the index of symmetry within or between the groups. Discussion Seventeen out of 20 participants tolerated and coped well with a 15-day clinical trial with curara® without any negative events. The primary outcome measures in this study showed significant improvements (10–20% of the baseline value) in both groups; however, contrary to our expectations, there were no significant differences between the groups. The same outcome was found for the BBS and TUG. When analyzing the RehaGait® data, significant intragroup differences in several parameters between days 0 and 14 were found in both groups. In particular, stride duration and cadence showed a more significant improvement in the curara®-wearing group compared to the non-curara®-wearing group (interaction effect: p = 0.006 for stride duration, p = 0.012 for cadence). As a result, the interaction effect for gait speed almost reached statistical significance ( p = 0.055). We reported previously that stride duration and cadence are increased in stroke patients when they walked with a curara® [ 13 ]. Thus, the rehabilitative effect of curara® on stride duration and cadence was confirmed in the present study. This effect is very likely to contribute to the improvement of walking speed, and the assistance provided by curara®, which shortened the gait cycle and enlarged the joint angles, would have led to this favorable change in stride duration and cadence. In this study, all the participants were rather mild in the severity of hemiparesis at baseline because they had to train with curara® (~ 5 kg) burdened when they were randomized to curara®-wearing group. In fact, the averaged gait speed was 0.90 m/sec at baseline ( n = 36), which was faster than the gait speed (0.08–0.64 m/s) in the participants reported in the meta-analysis study investigating the RAGT effect [ 14 ]. In our preliminary study on stroke patients, which was a single-use analysis of curara® type 3, the average walking speed of the subjects was 0.4 m/s ( n = 15) [ 13 ]. In this situation, we have to take the ceiling effect into consideration when interpreting the data, which is one of the major limitations of this study. As we measured the difference between the 10mWT on days 0 and 14, the ceiling effect should be minimized. The actual change in the 10mWT in group A (-0.23 ± 0.12 m/s, mean ± standard deviation) was greater than that in group B (-0.14 ± 0.12 m/s), but the difference between the groups was not statistically significant. Another concern was whether the assistance provided by curara® was best for each participant. We did not set synchronization gain at the hip and knee joints according to individual gait performance. Synchronization gain may be related to error learning that involves the trial and error required for motor learning [ 15 ]. A lower synchronization gain means a reduced degree of flexibility of intentional joint movement. Ideally the synchronization gain of curara® should be set individually, but it is a complicated and time-consuming process to perform during the limited time available for this clinical trial. During the study, we felt that the affinity of the participants to the robot varied from individual to individual. Roughly speaking, the more elderly individuals tended to have less affinity for curara® than the younger ones, and individuals with better walking ability had lower motivation to practice with the robot. One factor influencing affinity to the robot was that RAGT is still being developed as a method for stroke rehabilitation throughout Japan. For RAGT to become more popular, high-quality evidence should be acquired in future randomized case-control studies. At least, we can say that RAGT with curara® had a rehabilitative effect identical to that of therapist-assisted gait training. Our initial motive was to develop a wearable robot that elderly or handicapped people can use for gait rehabilitation in daily life. The results shown above are encouraging for us to improve curara® further. First, we need to improve its operability and user friendliness so that anybody can use it easily. At the present time, we are creating an advanced type of robot (curara® type 5) using the experience and knowledge acquired in this study. Furthermore, we need to identify the best application timing and assist conditions for curara® in stroke patients. Conclusion RAGT with curara® may help to improve the walking speed of stroke patients. In order to use curara® for walking rehabilitation in daily life, we have to review the selection criteria and outcomes of the subjects in future studies and further improve the operability and usability of curara®. List Of Abbreviations 6mWD 6-min walking distance 10mWT 10-m walking time BBS Berg Balance Scale RAGT robot-assisted gait training TUG timed up and go Declarations Ethics approval and consent to participate The study procedure was approved by the Ethics Committee of Shinshu University School of Medicine (No. 3999), and registered in the Japan Registry of Clinical Trials (Trial ID 032180163: https://jrct.niph.go.jp/en-latest-detail/jRCTs032180163) on February 27, 2019, and in the UMIN Clinical Trials Registry (UMIN000034237: https://center6.umin.ac.jp/cgi-open-bin/icdr/ctr_view.cgi?recptno=R000038939) on September 22, 2018. All participants were provided with all necessary information about the study and provided written informed consent before the clinical trial. All aspects of the study conformed to the principles described in the Declaration of Helsinki. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests Mr, Miyagawa, Dr. Matsushima, Mr. Maruyama and Mr. Tetsuya have no competing interests. Dr. Mizukami is funded by the Japan Society for the Promotion of Science (Grant-in-Aid for Young Scientists). Dr. Mizukami is funded by the Japan Society for the Promotion of Science grants (Grant-in-Aid for Scientific Research (C) and Challenging Research [Exploratory]), and was funded by the Japan Society for Promotion of Science grants (Grant-in-Aid for Scientific Research [B]), Tokyo Metropolitan Industrial Technology Research Institute grants (Robot industry activation business), and AMED grants (Robot care equipment development and standardization business). Dr. Yoshida is funded by Health and Labour Sciences Research Grants (Research Committee of the Ataxia, Research on Policy Planning and Evaluation for Rare and Intractable Diseases, The Ministry of Health, Labour, and Welfare, Japan). Funding This study was supported by the Japan Agency for Medical Research and Development (AMED) under Grant Number JP17hk0102048-19hk0102048. Authors’ contributions AM, MH and KY conceived the study. AM, YM, NM, MT, MH and KY contributed to study design. DM, AM, YM and KY contributed to data collection. DM and AM performed statistical analysis. DM, AM, YM and KY interpreted data. DM, AM and KY drafted the manuscript. DM, AM, YM, NM, MT, MH and KY revised and approved the final manuscript. Acknowledgments We thank to all the participants in this study and physical therapists and occupational therapists (JA Nagano Koseiren Kakeyu-Misayama Rehabilitation Center Kakeyu Hospital) for their professional help in RAGT and therapist-assisted gait training. We are also grateful to Ms. Yoshiko Takagi, Mr. Satoshi Hokari, Mr. Takashi Igarashi (The Center for Clinical Research, Shinshu University Hospital) for data management and monitoring of the study. A draft of this manuscript was edited by NAI, Inc. (Yokohama, Japan) References Ha YK, Joon HS, Sung PY, Min AS, Stephanie HL. Robot-assisted gait training for balance and lower extremity function in patients with infratentorial stroke: a single-blinded randomized controlled trial. J Neuroeng Rehabil. 2019;16:99. Finch IL, Barbeau H, Arsenault B. Influence of body weight support on normal human gait: development of a gait retraining strategy. Phys Ther. 1991;71:842–55. Hesse S, Uhlenbrock D. A mechanized gait trainer for restoration of gait. J Rehabil Res Dev.2000;37:701–8. Andreas M, Markus K, Ellen Q, Heinz M, Katrin F, Leopold S. Prospective, blinded, randomized crossover study of gait rehabilitation in stroke patients using the Lokomat gait orthosis. 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Geoffroy M, Romain G, David G, Bertrand G, Laurent B, Patrick D, et al.Effects of robotic gait training after stroke: A meta-analysis.Ann Phys Rehabil Med. 2020;63:518–534. Joseph H, Diane N, Marlena P, Kathy B, Donielle DC, Jennifer HK, et al. Multicenter randomized clinical trial evaluating the effectiveness of the Lokomat in subacute stroke. Neurorehabil Neural Repair. 2009;23:5–13. Additional Declarations Competing interest reported. Mr, Miyagawa, Dr. Matsushima, Mr. Maruyama and Mr. Tetsuya have no competing interests. Dr. Mizukami is funded by the Japan Society for the Promotion of Science (Grant-in-Aid for Young Scientists). Dr. Mizukami is funded by the Japan Society for the Promotion of Science grants (Grant-in-Aid for Scientific Research (C) and Challenging Research [Exploratory]), and was funded by the Japan Society for Promotion of Science grants (Grant-in-Aid for Scientific Research [B]), Tokyo Metropolitan Industrial Technology Research Institute grants (Robot industry activation business), and AMED grants (Robot care equipment development and standardization business). Dr. Yoshida is funded by Health and Labour Sciences Research Grants (Research Committee of the Ataxia, Research on Policy Planning and Evaluation for Rare and Intractable Diseases, The Ministry of Health, Labour, and Welfare, Japan). Cite Share Download PDF Status: Published Journal Publication published 28 Apr, 2023 Read the published version in Journal of NeuroEngineering and Rehabilitation → Version 2 posted Editorial decision: Major revision 02 Nov, 2022 Reviews received at journal 25 Jul, 2022 Reviewers agreed at journal 11 Jun, 2022 Reviewers invited by journal 08 Jun, 2022 Editor assigned by journal 17 May, 2022 Submission checks completed at journal 17 May, 2022 First submitted to journal 09 May, 2022 You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1592253","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[{"code":1,"date":"2022-05-03 14:14:20","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":109007480,"identity":"ffaacff0-87b5-4496-a6c3-72ba2a390f90","order_by":0,"name":"Daichi Miyagawa","email":"","orcid":"","institution":"JA Nagano Koseiren Kakeyu-Misayama Rehabilitation Center Kakeyu Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Daichi","middleName":"","lastName":"Miyagawa","suffix":""},{"id":109007481,"identity":"5a210f2d-ff41-44df-927f-2762edff78da","order_by":1,"name":"Akira Matsushima","email":"","orcid":"","institution":"JA Nagano Koseiren Kakeyu-Misayama Rehabilitation Center Kakeyu Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Akira","middleName":"","lastName":"Matsushima","suffix":""},{"id":109007482,"identity":"560072a0-af61-458b-936d-da9e562bf108","order_by":2,"name":"Yoichi Maruyama","email":"","orcid":"","institution":"JA Nagano Koseiren Kakeyu-Misayama Rehabilitation Center Kakeyu Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yoichi","middleName":"","lastName":"Maruyama","suffix":""},{"id":109007483,"identity":"5d7606ee-8b53-400b-a264-e1a91d579086","order_by":3,"name":"Noriaki Mizukami","email":"","orcid":"","institution":"International Professional University of Technology in Tokyo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Noriaki","middleName":"","lastName":"Mizukami","suffix":""},{"id":109007484,"identity":"f2af689f-4988-42b1-8029-30bf55c9e551","order_by":4,"name":"Mikio Tetsuya","email":"","orcid":"","institution":"AssistMotion Inc","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mikio","middleName":"","lastName":"Tetsuya","suffix":""},{"id":109007485,"identity":"35e357fd-0419-4c3b-8ffc-e7c80d00b1bd","order_by":5,"name":"Minoru Hashimoto","email":"","orcid":"","institution":"Shinshu University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Minoru","middleName":"","lastName":"Hashimoto","suffix":""},{"id":109007486,"identity":"b71e961d-0e8c-4eeb-a4d6-816ee8aacbd5","order_by":6,"name":"Kunihiro Yoshida","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBUlEQVRIiWNgGAWjYBACCSBmZjBgZuBn4GE4wABCEMBGWItkA2laQLoO8ID4B3CqhAPJGcmHPxcUWMsbnz978HDBnzuJDRIJjB9+MPDl4dIiLZGWJj3DIN1w2428hMMz256BtDBL9jCwFePSIieRY8bMY3CYcdsNIMnbcDhx/40EBmmgXxIbcGsx/gxUbL+5/4zBYZ4/h8G2/ManRVoix0AaqCVxA0MOUAsbWAsbXlske56lAbWkJ8+4AdTC23bYuIHnYZtljwFuv0gcB4YYzx9r2/7+M0AX/jks28CefPjGj4pjOEOMQSABQ4gR6CSDY5jiMMB/ALt4DW4to2AUjIJRMNIAAMTLVr8kbWdXAAAAAElFTkSuQmCC","orcid":"","institution":"Shinshu University School of Medicine","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Kunihiro","middleName":"","lastName":"Yoshida","suffix":""}],"badges":[],"createdAt":"2022-04-25 08:29:26","currentVersionCode":2,"declarations":"","doi":"10.21203/rs.3.rs-1592253/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-1592253/v2","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12984-023-01168-x","type":"published","date":"2023-04-28T20:35:06+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":44727262,"identity":"24551358-3e30-439d-aa9a-123e9af3ffed","added_by":"auto","created_at":"2023-10-16 20:52:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":426820,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1592253/v2/1dc25294-6f2b-415e-8d25-1393ea8d6819.pdf"}],"financialInterests":"Competing interest reported. Mr, Miyagawa, Dr. Matsushima, Mr. Maruyama and Mr. Tetsuya have no competing interests.\nDr. Mizukami is funded by the Japan Society for the Promotion of Science (Grant-in-Aid for Young Scientists).\nDr. Mizukami is funded by the Japan Society for the Promotion of Science grants (Grant-in-Aid for Scientific Research (C) and Challenging Research [Exploratory]), and was funded by the Japan Society for Promotion of Science grants (Grant-in-Aid for Scientific Research [B]), Tokyo Metropolitan Industrial Technology Research Institute grants (Robot industry activation business), and AMED grants (Robot care equipment development and standardization business).\nDr. Yoshida is funded by Health and Labour Sciences Research Grants (Research Committee of the Ataxia, Research on Policy Planning and Evaluation for Rare and Intractable Diseases, The Ministry of Health, Labour, and Welfare, Japan).","formattedTitle":"Gait training with a wearable curara ® robot during stroke rehabilitation: a randomized parallel-group trial","fulltext":[{"header":"Background","content":"\u003cp\u003eRecently, robot-assisted gait training (RAGT) has been applied widely to individuals with stroke to regain and improve walking ability [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In the 1990s, body weight-supported treadmill training was introduced in the clinical setting [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Currently, rehabilitation robots with different assistive forms for lower limb movements have become popular, e.g., Gait Trainer\u0026reg; and Haptic Walker\u0026reg;, which assist with foot movements, and Lokomat\u0026reg;, which assists with lower limb orthosis on a treadmill. These devices enable the joints of the lower limbs to move in a state close to normal during walking without voluntary efforts from the patient [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to stationary rehabilitation robots, wearable rehabilitation robots have been developed recently and used widely in gait training, e.g., Hybrid Assistive Limb (HAL\u0026reg;) and ReWALK\u0026reg; [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Generally, wearable rehabilitation robots are smaller and lighter than stationary rehabilitation robots; therefore, a great advantage of these devices is that individuals wearing them can move around freely. This makes it possible for people with a wearable rehabilitation robot to perform training in daily life. Systematic reviews have reported that rehabilitation robots improve balance and ankle spasticity in patients with brain diseases including stroke [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In a study investigating the rehabilitative effect of HAL\u0026reg;, the degree of walking independence evaluated by the Functional Ambulation Category was significantly improved in the HAL-wearing group compared to the non-wearing group [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe started clinical research in 2017 for the practical application of curara\u0026reg;, a wearable rehabilitation robot. We have examined the effect of curara\u0026reg; in patients with spinocerebellar degeneration [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and stroke [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. We have shown that the use of curara\u0026reg; improves walking speed, stride length, walking rate, and asymmetry in stroke patients [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], but we have not yet clarified its effect on gait training. Therefore, the purpose of this study was to examine the effect of curara\u0026reg; on gait training in stroke patients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eParticipants and instrumentation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 40 individuals participated in this study. They fulfilled all of the inclusion criteria and did not fulfill any of the exclusion criteria. The inclusion criteria were: (1) cerebrovascular disease presenting with hemiplegia; (2) aged ≥ 20 years; (3) 14–90 days after stroke onset; (4) able to walk ≥10 m independently with or without a walker and/or brace; and (5) Berg Balance Scale (BBS) score ≥ 26. The exclusion criteria were: (1) possible causes for gait disturbance other than cerebrovascular disease; (2) too thin or obese to fit into curara\u003csup\u003e®\u003c/sup\u003e; and (3) any other reasons that were considered to make the subjects ineligible to participate (for example, severe dementia or psychiatric symptoms, severe spasticity or joint contracture of the paralyzed leg, etc.).\u003c/p\u003e\n\u003cp\u003eThe participants were divided randomly into two groups (groups A and B). The participants in group A were assigned RAGT with curara\u003csup\u003e®\u003c/sup\u003e, whereas those in group B received conventional therapist-assisted gait training.\u0026nbsp;Treatment was randomly assigned at the Data Center of Center for Clinical Research in Shinshu University Hospital. The randomization list has been generated using Viedoc 4 ™ (Pharma Consulting Group, Sweden) that was used as an electronic data capture system for this study. To balance the two treatment arms, dynamic randomization performed between the two treatment arms in a ratio of 1:1 applying the modified algorithm of Pocock and Simon (as implemented in Viedoc).\u003c/p\u003e\n\u003cp\u003eWe used a wearable “curara\u003csup\u003e®\u003c/sup\u003e type 4” robot in this study, which weighs approximately 5 kg (four actuator units and the control box) and has a non-exoskeletal structure that does not have direct contact with the hip and knee joints. The basic mechanisms of curara\u003csup\u003e®\u003c/sup\u003e are characterized by a torque-sensing technique and synchronized-based control system. Detailed information regarding curara\u003csup\u003e®\u003c/sup\u003e is described in our previous reports [11, 13].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasurements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study period was 15 days in total. We evaluated the participants on days 0, 7, and 14. On these days, they were instructed to walk 10 m on a flat floor at a comfortable speed 9 times while wearing a RehaGait\u003csup\u003e®\u003c/sup\u003e analyzer (HASOMED, Magdeburg, Germany). We measured the 10-m walking time (10mWT) with a stopwatch. We collected the following gait parameters using RehaGait\u003csup\u003e®\u003c/sup\u003e: stride duration and length, standard deviation of stride duration and length, cadence, ratio of the stance/swing phases, minimum/maximum knee joint angle, and minimum/maximum hip joint angle. We also measured the 6-min walking distance (6mWD) and timed up and go (TUG) test on days 0, 7, and 14. We evaluated the BBS on days 0 and 14. We set the improvement rates of the 10mWT and 6mWD as the main outcome measures, which were calculated as the difference of values between days 14 and 0 divided by the value on day 0. All of the measurements shown above were acquired without wearing curara\u003csup\u003e®\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRehabilitation program\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGait training consisted of a 30 ± 5 min session each day through days 2–6 and days 8–13 (total, 12 days) for both groups. One or two physical therapists accompanied each participant during gait training. For group A, the therapists operated curara\u003csup\u003e®\u003c/sup\u003e and prevented falls, but they did not give any advice on gait to the participants. The participants also received a combination of physical (except gait training), occupational, or speech therapy rehabilitation. The maximum rehabilitation time including gait training with curara\u003csup\u003e®\u003c/sup\u003e was 3 h/day.\u003c/p\u003e\n\u003cp\u003eWe set synchronization gain, gait cycle, and joint angles as the assist conditions of curara\u003csup\u003e®\u003c/sup\u003e. Among these, synchronization gain was fixed to 0.1 at the hip joint and 0.3 at the knee joint throughout the rehabilitation period in all participants. The gait cycle and joint angles varied from individual to individual, and they were set according to the gait parameters of the fastest gait performance on days 0 and 7. The amplitude of the joint angle was set at 140% at the unaffected hip joint and 110% at the unaffected knee joint, and the gait cycle was set at 85%.\u0026nbsp;Therefore, the assist conditions were set 40% wider hip joint, 10% wider at the knee joint, and 15% faster in the gait cycle than the gait parameters of the fastest gait performance. The conditions set on day 0 were used for gait training on days 1–6, and those updated on day 7 were utilized on days 8–13. These parameters meant that the amount of assistance provided by the robot was larger at the hip joint than at the knee joint, i.e., the device-in-charge robotic support was more influential at the hip joint than at the knee joint. With these assist conditions, curara\u003csup\u003e®\u003c/sup\u003e enabled the participants to reproduce their best gait performance faithfully during gait training.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe distribution of characteristics of the participants between two groups\u0026nbsp;was\u0026nbsp;analyzed by a \u003cem\u003et\u003c/em\u003e-test for\u0026nbsp;continuous variables and a chi-square test for categorical data.\u0026nbsp;The differences of the BBS score and TUG test between days 0 and 14 were analyzed by a paired \u003cem\u003et\u003c/em\u003e-test. The differences of the gait parameters obtained with RehaGait\u003csup\u003e®\u003c/sup\u003e were analyzed using a generalized linear mixed model with Bonferroni’s correction. In the model, the day of measurement, group, and the interaction between those two factors were set as the fixed effects, and subject factors and the number of measurements on the same day of measurement were set as random effects. All statistical analyses were performed using IBM SPSS Statistics 24 for Windows. The level of significance was set at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 in all tests.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOf the 40 participants, three in group A and one in group B dropped out of the trial; two participants in group A retracted informed consent because of mental health issues and one discontinued the trial due to robot-induced skin problems, while one participant in group B had a second stroke during the trial period. A total of 36 participants (17 in group A and 19 in group B) completed the program without any negative events. Detailed information on the participants is shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. However, one participant in group B was excluded from the analysis due to extreme outliers in most of the measured items; therefore, the data of 35 participants were analyzed.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of the participants.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup A (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e\n \u003cp\u003emean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup B (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e\n \u003cp\u003emean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.1\u0026thinsp;\u0026plusmn;\u0026thinsp;12.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.0\u0026thinsp;\u0026plusmn;\u0026thinsp;12.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.631\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e162.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e166.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.204\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight (kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.2\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66.5\u0026thinsp;\u0026plusmn;\u0026thinsp;14.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.302\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLower limb length (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBrunnstrom Recovery Stage\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e#\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIII-VI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIV-VI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.916\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFIM score on day 0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.829\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBBS on day 0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eBBS: Berg Balance Scale; FIM: Functional Independence Measure; SD: standard deviation\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e\u003csup\u003e#\u003c/sup\u003eBrunnstrom Recovery Stage for lower legs\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eThe results of the main outcome measures are shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. The mean improvement rates of the 10mWT were 20.6% in group A and 13.9% in group B. However, the difference between both groups was not statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.099). The mean improvement rates of the 6mWD were 16.8% in group A and 19.4% in group B, again with no significant difference between both groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.067). There amount of change in the BBS or TUG was not statistically significant between groups A and B.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eResults of the main outcomes, BBS, and TUG\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup A (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e\n \u003cp\u003emean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup B (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e\n \u003cp\u003emean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eImprovement rate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e10mWT (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.6\u0026thinsp;\u0026plusmn;\u0026thinsp;11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6mWD (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16.8\u0026thinsp;\u0026plusmn;\u0026thinsp;18.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19.4\u0026thinsp;\u0026plusmn;\u0026thinsp;18.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.677\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmount of change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBBS (score)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTUG (s)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e10mWT: 10-m walking time; 6mWD: 6-min walking distance; BBS: Berg Balance Scale; SD: standard deviation; TUG: timed up and go\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eThe values of the gait parameters obtained by RehaGait\u0026reg; are shown in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. Almost all of the gait parameters, except maximum flexion angles of the knee joints, improved on day 14 in each group. When examining the interaction effect between the day of measurement and group, stride duration (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006) and cadence (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012) were more significantly improved in group A than in group B. These results were expected to be reflected in gait speed, and the interaction effect of gait speed was very close to the level of statistical significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.055).\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eGait parameters obtained with RehaGait\u0026reg;\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGroup A (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGroup B (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eday 0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eday 14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eday 0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eday 14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntragroup difference\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e#\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eInteraction\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eeffect\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup A\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup B\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eStride duration (s)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\" name=\"Emphasis\" type=\"BoldUnderline\"\u003e0.006\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eStride length (m)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.359\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGait speed (m/s)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\" name=\"Emphasis\" type=\"BoldUnderline\"\u003e0.055\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCadence (steps/min)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e103.1\u0026thinsp;\u0026plusmn;\u0026thinsp;14.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e116.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105.9\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e112.6\u0026thinsp;\u0026plusmn;\u0026thinsp;17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\" name=\"Emphasis\" type=\"BoldUnderline\"\u003e0.012\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRatio of the unaffected\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003estanding phase (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e64.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRatio of the affected\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003estanding phase (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e66.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e64.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaximum flexion angles\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eunaffected knee joint (\u0026deg;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56.4\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.695\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.449\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eaffected knee joint (\u0026deg;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60.1\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eunaffected hip joint (\u0026deg;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.376\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eaffected hip joint (\u0026deg;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymmetry\u003c/strong\u003e\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e\u003csup\u003e\u003cstrong\u003e#\u003c/strong\u003e\u003c/sup\u003eIntragroup difference between days 0 and 14.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e*Interaction effect: between the day of measurement and group.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e\u003csup\u003e\u0026sect;\u003c/sup\u003eSymmetry: ratio of the maximum flexion angles of the affected hip joint to the unaffected hip joint.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eThe index of symmetry was expressed as the ratio of the maximum hip flexion angle of the affected leg to that of the unaffected leg in each group (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). However, there was no significant difference in the index of symmetry within or between the groups.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSeventeen out of 20 participants tolerated and coped well with a 15-day clinical trial with curara\u0026reg; without any negative events. The primary outcome measures in this study showed significant improvements (10\u0026ndash;20% of the baseline value) in both groups; however, contrary to our expectations, there were no significant differences between the groups. The same outcome was found for the BBS and TUG.\u003c/p\u003e \u003cp\u003eWhen analyzing the RehaGait\u0026reg; data, significant intragroup differences in several parameters between days 0 and 14 were found in both groups. In particular, stride duration and cadence showed a more significant improvement in the curara\u0026reg;-wearing group compared to the non-curara\u0026reg;-wearing group (interaction effect: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006 for stride duration, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012 for cadence). As a result, the interaction effect for gait speed almost reached statistical significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.055). We reported previously that stride duration and cadence are increased in stroke patients when they walked with a curara\u0026reg; [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Thus, the rehabilitative effect of curara\u0026reg; on stride duration and cadence was confirmed in the present study. This effect is very likely to contribute to the improvement of walking speed, and the assistance provided by curara\u0026reg;, which shortened the gait cycle and enlarged the joint angles, would have led to this favorable change in stride duration and cadence.\u003c/p\u003e \u003cp\u003eIn this study, all the participants were rather mild in the severity of hemiparesis at baseline because they had to train with curara\u0026reg; (~\u0026thinsp;5 kg) burdened when they were randomized to curara\u0026reg;-wearing group. In fact, the averaged gait speed was 0.90 m/sec at baseline (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;36), which was faster than the gait speed (0.08\u0026ndash;0.64 m/s) in the participants reported in the meta-analysis study investigating the RAGT effect [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In our preliminary study on stroke patients, which was a single-use analysis of curara\u0026reg; type 3, the average walking speed of the subjects was 0.4 m/s (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;15) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In this situation, we have to take the ceiling effect into consideration when interpreting the data, which is one of the major limitations of this study. As we measured the difference between the 10mWT on days 0 and 14, the ceiling effect should be minimized. The actual change in the 10mWT in group A (-0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12 m/s, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation) was greater than that in group B (-0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12 m/s), but the difference between the groups was not statistically significant.\u003c/p\u003e \u003cp\u003eAnother concern was whether the assistance provided by curara\u0026reg; was best for each participant. We did not set synchronization gain at the hip and knee joints according to individual gait performance. Synchronization gain may be related to error learning that involves the trial and error required for motor learning [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. A lower synchronization gain means a reduced degree of flexibility of intentional joint movement. Ideally the synchronization gain of curara\u0026reg; should be set individually, but it is a complicated and time-consuming process to perform during the limited time available for this clinical trial.\u003c/p\u003e \u003cp\u003eDuring the study, we felt that the affinity of the participants to the robot varied from individual to individual. Roughly speaking, the more elderly individuals tended to have less affinity for curara\u0026reg; than the younger ones, and individuals with better walking ability had lower motivation to practice with the robot. One factor influencing affinity to the robot was that RAGT is still being developed as a method for stroke rehabilitation throughout Japan. For RAGT to become more popular, high-quality evidence should be acquired in future randomized case-control studies.\u003c/p\u003e \u003cp\u003eAt least, we can say that RAGT with curara\u0026reg; had a rehabilitative effect identical to that of therapist-assisted gait training. Our initial motive was to develop a wearable robot that elderly or handicapped people can use for gait rehabilitation in daily life. The results shown above are encouraging for us to improve curara\u0026reg; further. First, we need to improve its operability and user friendliness so that anybody can use it easily. At the present time, we are creating an advanced type of robot (curara\u0026reg; type 5) using the experience and knowledge acquired in this study. Furthermore, we need to identify the best application timing and assist conditions for curara\u0026reg; in stroke patients.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eRAGT with curara\u0026reg; may help to improve the walking speed of stroke patients. In order to use curara\u0026reg; for walking rehabilitation in daily life, we have to review the selection criteria and outcomes of the subjects in future studies and further improve the operability and usability of curara\u0026reg;.\u003c/p\u003e"},{"header":"List Of Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e6mWD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e6-min walking distance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e10mWT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e10-m walking time\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBerg Balance Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRAGT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003erobot-assisted gait training\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTUG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etimed up and go\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study procedure was approved by the Ethics Committee of Shinshu University School of Medicine (No. 3999), and registered in the Japan Registry of Clinical Trials (Trial ID 032180163: https://jrct.niph.go.jp/en-latest-detail/jRCTs032180163) on February 27, 2019, and in the UMIN Clinical Trials Registry (UMIN000034237: https://center6.umin.ac.jp/cgi-open-bin/icdr/ctr_view.cgi?recptno=R000038939) on September 22, 2018. All participants were provided with all necessary information about the study and provided written informed consent before the clinical trial. All aspects of the study conformed to the principles described in the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMr, Miyagawa, Dr. Matsushima, Mr. Maruyama and Mr. Tetsuya have no competing interests.\u003c/p\u003e\n\u003cp\u003eDr. Mizukami is funded by the Japan Society for the Promotion of Science (Grant-in-Aid for Young Scientists).\u003c/p\u003e\n\u003cp\u003eDr. Mizukami is funded by the Japan Society for the Promotion of Science grants (Grant-in-Aid for Scientific Research (C) and Challenging Research [Exploratory]), and was funded by the Japan Society for Promotion of Science grants (Grant-in-Aid for Scientific Research [B]), Tokyo Metropolitan Industrial Technology Research Institute grants (Robot industry activation business), and AMED grants (Robot care equipment development and standardization business).\u003c/p\u003e\n\u003cp\u003eDr. Yoshida is funded by Health and Labour Sciences Research Grants (Research Committee of the Ataxia, Research on Policy Planning and Evaluation for Rare and Intractable Diseases, The Ministry of Health, Labour, and Welfare, Japan).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Japan Agency for Medical Research and\u0026nbsp;Development (AMED) under Grant\u0026nbsp;Number JP17hk0102048-19hk0102048.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAM, MH and KY conceived the study. AM, YM, NM, MT, MH and KY contributed to study design. DM, AM, YM and KY contributed to data collection. DM and AM performed statistical analysis. DM, AM, YM and KY interpreted data. DM, AM and KY drafted the manuscript. DM, AM, YM, NM, MT, MH and KY revised and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank to all the participants in this study and physical therapists and occupational therapists (JA Nagano Koseiren Kakeyu-Misayama Rehabilitation Center Kakeyu Hospital) for their professional help in RAGT and therapist-assisted gait training. We are also grateful to Ms. Yoshiko Takagi, Mr. Satoshi Hokari, Mr. Takashi Igarashi (The Center for Clinical Research, Shinshu University Hospital) for data management and monitoring of the study. A draft of this manuscript was edited by NAI, Inc. (Yokohama, Japan)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHa YK, Joon HS, Sung PY, Min AS, Stephanie HL. Robot-assisted gait training for balance and lower extremity function in patients with infratentorial stroke: a single-blinded randomized controlled trial. J Neuroeng Rehabil. 2019;16:99.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFinch IL, Barbeau H, Arsenault B. Influence of body weight support on normal human gait: development of a gait retraining strategy. Phys Ther. 1991;71:842\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHesse S, Uhlenbrock D. A mechanized gait trainer for restoration of gait. J Rehabil Res Dev.2000;37:701\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndreas M, Markus K, Ellen Q, Heinz M, Katrin F, Leopold S. Prospective, blinded, randomized crossover study of gait rehabilitation in stroke patients using the Lokomat gait orthosis. Neurorehabil Neural Repair.2007;21:307\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchmidt H, Hesse S, Bernhardt R, Kr\u0026uuml;ger J. Haptic Walker a novel haptic foot device. April 2005ACM Transactions on Applied Perception 2:166\u0026ndash;180.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUriel MH, Benjamin M, Tareq A, Leen J, James M, Dingguo Z.Wearable Assistive Robotics: A Perspective on Current Challenges and Future Trends. Sensors (Basel). 2021;21:6751.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQing XZ, Li G, Carol CW, Qi SM, Yan TL, Ping PH, et al. Robot-assisted therapy for balance function rehabilitation after stroke: A systematic review and meta-analysis. Int J Nurs Stud. 2019;95:7\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShakti D, Mathew L, Kumar N, Kataria C. Effectiveness of robo-assisted lower limb rehabilitation for spastic patients: A systematic review. Biosens Bioelectron. 2018;117:403\u0026ndash;415.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWatanabe H, Tanaka N, Inuta T, Saitou H, Yanagi H. Locomotion improvement using a hybrid assistive limb in recovery phase stroke patients: a randomized controlled pilot study. Arch Phys Med Rehabil.2014;95:2006\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWatanabe H, Goto R, Tanaka N, Matsumura A, Yanagi H. Effects of gait training using the Hybrid Assistive Limb\u0026reg; in recovery-phase stroke patients: A 2-month follow-up, randomized, controlled study. NeuroRehabilitation. 2017;40:363\u0026ndash;367.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsukahara A, Yoshida K, Matsushima A, Ajima K, Kuroda C, Mizukami N, et al. Effects of gait support in patients with spinocerebellar degeneration by a wearable robot based on synchronization control. J NeuroEng Rehabili. 2018;15:84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatsushima A, Maruyama Y, Mizukami N, Tetsuya M, Hashimoto M, Yoshida K. Gait training with a wearable curara\u0026reg; robot for cerebellar ataxia: a single-arm study. Biomed Eng Online. 2021;20:90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMizukami N, Takeuchi S, Tetsuya M, Tsukahara A, Hashimoto M, Yoshida K, et al. Effect of the synchronization-based control of a wearable robot having a non-exoskeletal structure on the hemiplegic gait of stroke patients. IEEE Trans Neural Syst Rehabil Eng. 2018;26:1011\u0026ndash;1016.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGeoffroy M, Romain G, David G, Bertrand G, Laurent B, Patrick D, et al.Effects of robotic gait training after stroke: A meta-analysis.Ann Phys Rehabil Med. 2020;63:518\u0026ndash;534.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoseph H, Diane N, Marlena P, Kathy B, Donielle DC, Jennifer HK, et al. Multicenter randomized clinical trial evaluating the effectiveness of the Lokomat in subacute stroke. Neurorehabil Neural Repair. 2009;23:5\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuroengineering-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jner","sideBox":"Learn more about [Journal of NeuroEngineering and Rehabilitation](http://jneuroengrehab.biomedcentral.com/)","snPcode":"12984","submissionUrl":"https://submission.nature.com/new-submission/12984/3","title":"Journal of NeuroEngineering and Rehabilitation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"robot-assisted gait training, stroke rehabilitation, randomized controlled trial, motor learning, hemiparesis","lastPublishedDoi":"10.21203/rs.3.rs-1592253/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1592253/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eRecently, robot-assisted gait training (RAGT) has been applied widely to individuals with stroke to regain and improve walking ability. We have developed a non-exoskeleton rehabilitation robot, “curara\u003csup\u003e®\u003c/sup\u003e,” and examined its immediate effect in patients with spinocerebellar degeneration and stroke, but its rehabilitative effect has not been clarified. The purpose of this study was to examine the effect of curara\u003csup\u003e®\u003c/sup\u003e on gait training in stroke patients.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eForty stroke patients were enrolled in this study. The participants were divided randomly into two groups (groups A and B). The subjects in group A were assigned RAGT with curara\u003csup\u003e®\u003c/sup\u003e type 4, whereas those in group B received conventional therapist-assisted gait training. The clinical trial period was 15 days. The 10-m walking time (10mWT), 6-min walking distance (6mWD), timed up and go test, and gait parameters (stride duration and length, standard deviation of stride duration and length, cadence, ratio of the stance/swing phases, minimum/maximum knee joint angle, and minimum/maximum hip joint angle) were measured using a RehaGait\u003csup\u003e®\u003c/sup\u003e analyzer. The Berg Balance Scale was evaluated on days 0 and 14. Gait training was performed for 30 ± 5 min per day through days 2–6 and days 8–13 (total, 12 days) in both groups. The improvement rate was calculated as the difference of values between days 14 and 0 divided by the value on day 0. The improvement rates of the 10mWT and 6mWD were set as the main outcomes.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe data of 35 participants were analyzed. There was no significant difference in the main outcomes between both groups. As for intragroup changes, gait speed, stride length, stride duration, and cadence were improved significantly between days 0 and 14 in each group. There was no significant difference between the measured joint angle and the left-right angle ratio of symmetry within or between the groups. When assessing the interaction effect between the day of measurement and group, stride duration and cadence were more significantly improved in group A than in group B.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eThe wearable curara\u003csup\u003e®\u003c/sup\u003e robot has the potential to improve gait function during stroke rehabilitation.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTrial registration\u003c/strong\u003e: Japan Registry of Clinical Trials (jRCTs032180163). Registered on February 22, 2019; https://jrct.niph.go.jp/en-latest-detail/jRCTs032180163\u003c/p\u003e\u003cp\u003eUMIN Clinical Trials Registry (UMIN000034237). Registered on September 22, 2018; https://center6.umin.ac.jp/cgi-open-bin/icdr/ctr_view.cgi?recptno=R000038939\u003c/p\u003e","manuscriptTitle":"Gait training with a wearable curara ® robot during stroke rehabilitation: a randomized parallel-group trial","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2022-05-27 19:08:33","doi":"10.21203/rs.3.rs-1592253/v2","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-11-02T15:05:41+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-07-25T16:46:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"69511e9d-6725-435d-9c61-355d6b36fb48","date":"2022-06-11T15:07:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-06-08T14:24:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-05-17T06:25:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-05-17T06:24:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of NeuroEngineering and Rehabilitation","date":"2022-05-10T01:57:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuroengineering-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jner","sideBox":"Learn more about [Journal of NeuroEngineering and Rehabilitation](http://jneuroengrehab.biomedcentral.com/)","snPcode":"12984","submissionUrl":"https://submission.nature.com/new-submission/12984/3","title":"Journal of NeuroEngineering and Rehabilitation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c4f3c126-6f7b-4674-850c-59b4d2a33271","owner":[],"postedDate":"May 27th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T20:44:43+00:00","versionOfRecord":{"articleIdentity":"rs-1592253","link":"https://doi.org/10.1186/s12984-023-01168-x","journal":{"identity":"journal-of-neuroengineering-and-rehabilitation","isVorOnly":false,"title":"Journal of NeuroEngineering and Rehabilitation"},"publishedOn":"2023-04-28 20:35:06","publishedOnDateReadable":"April 28th, 2023"},"versionCreatedAt":"2022-05-27 19:08:33","video":"","vorDoi":"10.1186/s12984-023-01168-x","vorDoiUrl":"https://doi.org/10.1186/s12984-023-01168-x","workflowStages":[]},"version":"v2","identity":"rs-1592253","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1592253","identity":"rs-1592253","version":["v2"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}