Robot-Assisted Gait Training in Individuals With Spinal Cord Injury: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Robot-Assisted Gait Training in Spinal Cord Injury

Article information

Ann Rehabil Med. 2024;48(3):171-191

Publication date (electronic) : 2024 June 28

doi : https://doi.org/10.5535/arm.230039

Jong Mi Park, MD ¹

, Yong Wook Kim, MD, PhD ²

, Su Ji Lee, MD ²

, Ji Cheol Shin, MD, PhD^,²

¹Department of Physical Medicine and Rehabilitation, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Korea

²Department and Research Institute of Rehabilitation Medicine, Yonsei University College of Medicine, Seoul, Korea

Correspondence: Ji Cheol Shin Department of Rehabilitation Medicine, Yonsei University Medical Center, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea. Tel: +82-2-2228-3713 Fax: +82-2-2228-3710 E-mail: jcsevrm@yuhs.ac

Received 2023 December 28; Revised 2024 April 19; Accepted 2024 May 22.

Abstract

Spinal cord injury (SCI) rehabilitation emphasizes locomotion. Robotic-assisted gait training (RAGT) is widely used in clinical settings because of its benefits; however, its efficacy remains controversial. We conducted a systematic review and meta-analysis to investigate the efficacy of RAGT in patients with SCI. We searched international and domestic databases for articles published until April 18, 2024. The meta-analysis employed a random effects model to determine the effect size as either mean difference (MD) or standardized MD (SMD). Evidence quality was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Twenty-three studies with a total of 690 participants were included in the final analysis. The overall pooled effect size for improvement in activities of daily living was 0.24, with SMD (95% confidence interval [95% CI], 0.04–0.43; GRADE: high) favoring RAGT over conventional rehabilitation. Muscular strength (MD, 0.23; 95% CI, 0.02–0.44; GRADE: high), walking index for SCI (MD, 0.31; 95% CI, 0.07–0.55; GRADE: moderate) and 6 min walk test distance (MD, 0.38; 95% CI, 0.14–0.63; GRADE: moderate) showed significant improvement in the robot group. Subgroup analysis revealed that subacute patients and intervention periods >2 months were more effective. This meta-analysis revealed that RAGT significantly improved activities of daily living, muscular strength, and walking abilities. Additional studies are needed to identify the optimal treatment protocol and specific patient groups for which the protocol is most effective.

Keywords: Spinal cord injuries; Robotics; Locomotion; Gait; Recovery of function

GRAPHICAL ABSTRACT

INTRODUCTION

Spinal cord injury (SCI) can cause various impairments in sensory, motor, and autonomic functions below the level of injury. This results in muscle weakness and atrophy, gait disturbances, sensory dysfunctions, and autonomic dysfunction [1]. Rehabilitation has focused on locomotion, especially for individuals with incomplete SCI classified as C or D on the American Spinal Injury Association (ASIA) Impairment Scale, because they are more likely to regain functional gait [2]. Early gait rehabilitation programs used manually assisted overground training with manual contact by a therapist, which later evolved into body weight-supported treadmill training. Since the introduction of the Lokomat (Hocoma AG) in the late 1990s, gait training with robots has gained traction, and is increasingly being used clinically because of its ability to perform high-intensity, repetitive movements for consistent periods of time, and is less demanding on the therapist [3].

With advancements in robotic technology, various types of robots are being utilized clinically, which can be broadly divided into three categories: exoskeleton treadmill training, wearable exoskeleton, and end-effector robots. Grounded exoskeleton robots have two programmable robotic joints in each leg, and are designed to support hip and knee movement when walking on a treadmill while supporting the body weight with a harness, with Lokomat being a prime example [3]. Wearable exoskeleton robots are ground walking systems that use a rigid external frame to support the lower limbs and torso while assisting movements at the hip and knee joints. They can be trained across a range of environments, including indoor and outdoor settings, as well as with obstacles and stairs. Examples include Ekso (Ekso Bionics), HANK (Gogoa Mobility), AIDER (Buffalo Robot Technology), and ReWalk (ReWalk Robotics) [4,5]. The end effector robot has a footplate attached with a walking trajectory only for the patient’s feet, allowing the knees and hips to move freely. Examples include Morning Walk (Curexo) and G-EO systems (Reha Technology) [6,7].

In 2021, the Korea Institute of Health and Medical Research analyzed the clinical utility of robotic-assisted gait training (RAGT) compared to that of conventional rehabilitation in patients with SCI. No statistically significant differences were observed in walking ability, muscle strength, functional performance, spasticity, balance, and quality of life [8]. As the number of relevant studies has grown, subsequent meta-analyses of the international literature have shown that RAGT significantly improves spasticity, walking ability, distance, speed, function, and peak oxygen consumption [9-11]. However, no studies have analyzed the effects of the type of robot, intervention duration, or onset period. We aimed to obtain data from randomized clinical trials conducted so far and dissect them based on robot classification, intervention duration, and onset period, with the aim of offering a comprehensive overview of the efficacy of RAGT in patients with SCI. We also hope that this study will support future policy decisions in the medical technology sector and contribute to adequate health insurance coverage.

METHODS

This meta-analysis adhered to the guidelines outlined in the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement [12]. Supplementary Material S1 includes the PRISMA checklist. Additionally, the review protocol was registered and assigned the registration number CRD42023475357 in the International Prospective Register of Systematic Reviews.

Search strategy

The systematic search was conducted in six international (PubMed, Embase, Cochrane library, Scopus, Web of Science, and Google Scholar) and five domestic (KoreaMed, KMBase, KISS, RISS, and NDSL) databases until October 5, 2023, and we updated our search on April 18, 2024. The search formula was as follows: (Gait OR “Gait disorder” OR walking OR “Lower Extremity” OR leg or foot or ankle or tibia or fibula or femur or thigh or lower limb) AND (paresis OR paralysis or hemiplegia or paraplegia) AND (Robotics OR automation OR computer-assisted) AND (rehabilitation OR “Physical Therapy Modalities” OR “Exercise Therapy” OR physical therapy or physiotherapy or kinesitherapy or exercise) AND (“spinal cord injury” OR SCI) (Supplementary Material S2). We selected all published randomized controlled trials (RCTs) that compare RAGT with conventional rehabilitation methods. No data or language restrictions were applied. Two reviewers (JMP and JCS) independently reviewed titles and abstracts.

Study selection and data extraction

The study inclusion criteria adhered to the PICOS (Population, Intervention, Comparison, Outcomes, Study design) framework. The target population comprised patients with SCI and gait impairment. The intended intervention involved RAGT. For comparison, we established a control group of patients who received standard physical therapy with a therapist or non-robotic device therapy as traditional rehabilitation treatment. Designated outcomes comprised several primary outcomes encompassing activities of daily living (functional independence measure [FIM], spinal cord independence measurement [SCIM], and modified Barthel index [MBI]), muscular strength (lower extremity motor score, LEMS), spasticity (modified Ashworth scale, MAS), and balance (Berg balance scale, BBS), and walking ability (walking index for SCI [WISCI], 10 meter walk test [10MWT] speed, 6 min walk test [6MWT] distance, and step length). Secondary outcomes included body composition (body mass, lean tissue, and fat tissue) and cardiopulmonary function (forced expiratory volume in the first second [FEV1], forced vital capacity [FVC], heart rate, and peak cough flow [PCF]). The study design specifically included RCTs, excluding non-human studies, cohort studies, case reports, and studies that did not conform to the PICOS framework.

Two reviewers (JMP and YWK) independently extracted relevant data, including the name of the first author, year of publication, patient demographic data, mean age, sample size, type of intervention (robot type), intervention protocol, control protocol, and outcomes. Information extraction was facilitated by ImageJ software version 1.53 (ImageJ software; National Institutes of Health, https://imagej.nih.gov) in instances where the study estimates were solely presented graphically without numerical reporting.

Quality assessment and GRADE evaluation

The quality of studies was assessed using the Revised Cochrane Risk of Bias Tool for Randomized Trials (RoB2), which identified potential bias risks. The RoB2 comprises five elements: the randomization process, deviations from intended interventions, missing outcome data, outcome measurement, and selection of reported results. Each element was appraised for low risk of bias, concerns of bias, high risk of bias, or lack of information [13]. Two reviewers (JMP and YWK) independently assessed the risk of bias, and disagreements regarding the quality assessment were resolved through discussion with a third reviewer (JCS).

The certainty of evidence in the included meta-analyses was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) tool, which comprises five domains: (1) risk of bias; (2) inconsistency; (3) indirectness; (4) imprecision; and (5) publication bias. Ratings for certainty of evidence were high, moderate, low, and very low [14].

Statistical analysis

In this meta-analysis, we conducted a statistical standardization of the effect sizes related to RAGT in patients with SCI. Initially, we calculated the mean and standard deviation (SD) of the change-from-baseline values for intervention and control groups. For studies lacking complete data, the mean and SD values of the change-from-baseline were computed, according to the guidelines outlined in Section 6 of the Cochrane Handbook (version 6.3). Effect sizes were calculated as mean difference (MD) and standardized MD (SMD), with 95% confidence interval (95% CI) within a random effects model. The included studies were from different countries and populations with different medical backgrounds; therefore, we conducted a restricted maximum likelihood random effects meta-analysis to account for an expected high level of heterogeneity [15]. Heterogeneity between studies was evaluated using the I² metric for inconsistency and Cochrane Q test p-values. As suggested in previous studies [16,17] we assessed publication bias only in meta-analyses of ≥3 studies using funnel plots and Egger’s test. All statistical analyses were performed using Stata version 18 (StataCorp LP). Two-sided statistical tests were used, and significance was set at p<0.05. Subgroup analyses were performed according to robot type (treadmill training robot [Lokomat], wearable gait robot [Ekso, HANK, AIDER], end effector gait robot [morning walk]), intervention period, and onset period.

RESULTS

Study identification and characteristics

We screened 980 studies from international databases and 5,485 studies from domestic databases, excluding 102 and 334 duplicate records, respectively. After screening the titles and abstracts, 51 studies were selected from international and domestic databases, and their full texts were screened. Of these, 35 studies were excluded for various reasons (study protocol, observational study, review article, insufficient detail in the data, inappropriate intervention, and inappropriate control), and seven articles found through citation searches were combined, resulting in 23 studies that were finally included in the meta-analysis. Fig. 1 shows a flowchart outlining the study selection process. This meta-analysis included 690 patients with SCI: 346 and 344 in the intervention and control groups, respectively. The number of participants included in a single study ranged between 7 [18] and 88 [19]. The average age of the participants was between 8.4 [20] and 59.6 years [21]. The average onset duration of the participants was between 20 [22] and 7,665 days [23]. Overall characteristics of the included studies are summarized in Table 1 [18-40].

Fig. 1.

Screening and selecting studies using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart.

Table 1.

Characteristics of the included studies

Assessment of risk and publication biases

Of the 23 RCTs, two showed high risk [24,25], but the rest showed some risk of concern. In all but one study [25], the randomization process and allocation were well described. Because the comparison was between RAGT and conventional standard physical treatment, all participants were aware of the intervention; therefore, bias due to deviations from the intended intervention was of some concern in all the studies. Approximately half of the studies (12 studies) showed a low risk of bias due to missing outcome data. In 11 studies (just under half of the included studies), outcome measure assessments were blinded to the intervention type, suggesting a low risk of outcome measure bias. Fourteen studies (more than half) pre-registered their study protocols and no data were duplicated, resulting in a low risk of bias in the selection of the reported results. Fig. 2 presents a traffic light diagram for each study included in the evaluation.

Fig. 2.

Traffic light diagram for the risk of bias of included studies as assessed using the Cochrane Risk of Bias 2.0 tool.

In Supplementary Fig. S1 illustrates the funnel plot, which displays the publication bias for each meta-analysis. We also checked for publication bias using the Eager test, as shown in Table 2. All analyses showed no significant publication bias, except for the step length and peak expiratory flow.

Table 2.

Summary of the findings and quality of evidence assessment using the GRADE approach

Effects of RAGT on activities of daily living

Activities of daily living, as measured using the FIM, SCIM, and MBI assessment tools, were reported in 11 studies. The overall meta-analysis showed significant improvement in the robot groups (SMD, 0.24; 95% CI, 0.04–0.43; I²=0%; p=0.02). When we analyzed the subgroups according to robot type, we found no significant difference in end-effector and wearable robots, but there was a statistically significant improvement in the Lokomat, a treadmill training robot (SMD, 0.29; 95% CI, 0.09–0.50; I²=0%; p=0.01; Fig. 3A). Activities of daily living quality of evidence was estimated to be high, according to the GRADE system (Table 2).

Fig. 3.

Meta-analysis of the effects of RAGT in patients with spinal cord injury (SCI). (A) Activities of daily living. (B) Muscular strength. (C) Spasticity. (D) Balance.

Effects of RAGT on muscular strength

Muscular strength measured using LEMS has been reported in 12 studies. The overall meta-analysis showed significant improvement in the robot groups (MD, 0.23; 95% CI, 0.02–0.44; I²=0%; p=0.03). Subgroup analysis according to robot type showed no significant difference in the end-effector and wearable robots, but a statistically significant improvement was observed in the Lokomat one (MD, 0.26; 95% CI, 0.03–0.49; I²=0%; p=0.03; Fig. 3B). The quality of evidence for muscular strength was estimated to be high using the GRADE system (Table 2).

Effects of RAGT on spasticity

Spasticity measured using the MAS was reported in three studies. The overall meta-analysis showed no significant difference (MD, -0.05; 95% CI, -0.37 to 0.28; I²=0%; p=0.77; Fig. 3C). The spasticity quality of evidence was estimated as low performing using the GRADE system (based on risk of bias and imprecision) (Table 2).

Effects of RAGT on balance

Balance, measured using the BBS, was reported in three studies. The overall meta-analysis showed no significant difference (MD, 0.44; 95% CI, -0.18 to 1.06; I²=33.42%; p=0.16). Subgroup analysis by robot type showed no significant difference in the Lokomat, but a statistically significant improvement was observed for end-effector robot (MD, 0.95; 95% CI, 0.17–1.72; I²=uncheckable; p=0.02; Fig. 3D). The balance quality of evidence was estimated as low performing using the GRADE system (based on inconsistency and imprecision) (Table 2).

Effects of RAGT on walking ability

Ten studies reported the WISCI, and the overall meta-analysis showed significant improvement in the robot group (MD, 0.31; 95% CI, 0.07–0.55; I²=30.67%; p=0.01). Subgroup analysis according to robot type showed no significant difference in the Lokomat, but there was statistically significant improvement in the end-effector and wearable robots, with a larger effect size for wearable robots (MD, 1.30; 95% CI, 0.35–2.25; I²=uncheckable; p=0.01; Fig. 4A). The WISCI quality of evidence was estimated to be moderate, according to the GRADE system (based on risk of bias) (Table 2).

Fig. 4.

Meta-analysis of the effects of RAGT on walking ability in patients with spinal cord injury (SCI). (A) Walking index for spinal cord injury (WISCI). (B) 10-min walk test (10MWT) Speed (m/s).

Thirteen studies reported 10MWT Speed, and the overall meta-analysis showed no significant difference (MD, -0.02; 95% CI, -0.46 to 0.42; I²=73.44%; p=0.91). Subgroup analysis according to robot type showed no significant differences between the end-effector, Lokomat, and wearable robots (Fig. 4B). The 10MWT Speed quality of evidence was estimated to be very low when the GRADE system was used (based on risk of bias, inconsistency, indirectness, and imprecision) (Table 2).

Ten studies reported 6MWT distance, and the overall meta-analysis showed significant improvement in the robot group (MD, 0.38; 95% CI, 0.14–0.63; I²=0%; p=0.00). Subgroup analysis according to robot type showed no significant difference in the end-effector and wearable robots, but a statistically significant improvement was observed in the Lokomat (MD, 0.40; 95% CI, 0.10–0.70; I²=0%; p=0.01; Fig. 5A). The 6MWT distance quality of evidence was estimated to be moderate, according to the GRADE system (based on risk of bias) (Table 2).

Fig. 5.

Meta-analysis of the effects of the RAGT on walking ability in patients with spinal cord injury (SCI). (A) 6-min walk test (6MWT) Distance (m). (B) Step length (m).

Two studies reported step length, and the overall meta-analysis showed no significant difference (MD, -0.15; 95% CI, -0.84 to 0.55; I²=0%; p=0.68). Subgroup analysis according to robot type showed no significant differences between the Lokomat and wearable robots (Fig. 5B). The step length quality of evidence was estimated to be low when using the GRADE system (based on imprecision and publication bias) (Table 2).

Effects of RAGT on body composition

Two studies reported body mass, and the overall meta-analysis showed no significant difference (MD, 0.02; 95% CI, -0.67 to 0.71; I²=0%; p=0.96). Two studies reported lean mass, and the overall meta-analysis showed no significant difference (MD, 0.02; 95% CI, -0.67 to 0.72; I²=0%; p=0.95). Two studies reported fat tissue percentage, and the overall meta-analysis showed no significant difference (MD, 0.09; 95% CI, -0.60 to 0.79; I²=0%; p=0.79). The quality of evidence for each sub-analysis of body composition was rated as moderate (based on imprecision) using the GRADE system (Fig. 6A, Table 2).

Fig. 6.

Meta-analysis of the effects of the RAGT in patients with spinal cord injury (SCI). (A) Body composition. (B) Cardiopulmonary function.

Effects of RAGT on cardiopulmonary function

Two studies reported FEV1, and the overall meta-analysis showed no significant difference (MD, 0.49; 95% CI, -0.20 to 1.18; I²=0%; p=0.17). Two studies reported FVC, and the overall meta-analysis showed no significant difference (MD, 0.33; 95% CI, -0.35 to 1.02; I²=0%; p=0.34). Two studies reported heart rate, and the overall meta-analysis showed no significant difference (MD, 0.56; 95% CI, -0.17 to 1.30; I²=10.09%; p=0.13). Two studies reported PCF, and the overall meta-analysis showed no significant difference (MD, 0.26; 95% CI, -0.41 to 0.94; I²=0%; p=0.44). In the sub-analysis of cardiopulmonary function, the quality of evidence was assessed using the GRADE system, with only peak expiratory flow rated low (based on imprecision and publication bias) and the rest rated moderate (based on imprecision) (Fig. 6B, Table 2).

Subgroup analysis

Subgroup analyses were performed based on intervention period and onset duration (Supplementary Fig. S2, Table 3). Subgroup analysis according to intervention duration showed significant improvements in activities of daily living difference (SMD, 0.34; 95% CI, 0.09–0.60; I²=0%; p=0.01; Supplementary Fig. S2A) and WISCI (MD, 0.33; 95% CI, 0.07–0.60; I²=0%; p=0.01; Supplementary Fig. S2E) in the group that intervened for >2 months. The 6MWT distance showed significant improvement in intervention periods of <1 month (MD, 0.59; 95% CI, 0.10–1.07; I²=23.92%; p=0.02) and >2 months (MD, 0.38; 95% CI, 0.04–0.72; I²=0%; p=0.03; Supplementary Fig. S2I).

Table 3.

Subgroup analysis

Onset duration was categorized as acute (0–3 months), subacute (4–12 months), and chronic (>12 months). When sub-analyzed according to onset duration, patients in the subacute phase had significant improvements in activities of daily living (SMD, 0.37; 95% CI, 0.03–0.70; I²=0%; p=0.03; Supplementary Fig. S2B) and WISCI (MD, 0.51; 95% CI, 0.06–0.96; I²=35.72%; p=0.03; Supplementary Fig. S2F). The 6MWT distance showed significant improvement in acute patients (MD, 0.69; 95% CI, 0.06–1.32; I²=38.51%; p=0.03; Supplementary Fig. S2J).

Adverse events

Six [18,26-30] of the 23 studies reported no adverse events. A variety of adverse events were reported in five studies [23,31-34], of which four [23,31,33,34] reported skin abrasions at the site of the robot, which improved with the application of pads at the time of treatment. Additionally, three studies [32-34] reported musculoskeletal pain, particularly knee and neck pain; one study [33] reported possibly related numbness; and one study [34] reported fatigue. The remaining 12 studies did not mention safety or side effects.

DISCUSSION

This systematic review investigated the efficacy of RAGT in patients with SCI. A study showed a high level of evidence that RAGT significantly improves activities of daily living and muscle strength. RAGT has been shown to significantly improve walking ability, specifically WISCI and 6MWT distances. Spasticity, balance, body composition, and cardiopulmonary function did not differ significantly between RAGT and conventional rehabilitation groups. Subgroup analyses showed significant improvements in activities of daily living and WISCI in subacute patients with onset duration of 4–12 months and intervention duration of ≥2 months.

The mechanism by which RAGT improves functionality in patients with SCI involves reinforcing proprioceptive input to the spinal cord through walking-related rhythmic movements facilitated by robots. This process activates the central pattern generator embedded within the lumbosacral spinal cord and can induce plastic changes at the spinal cord level and within the sensorimotor cortex (S1 and S2) and cerebellar regions of the brain [41-44].

When analyzing the effects of robot type, the results were heterogeneous. For activities of daily living and muscular strength, the Lokomat had the largest effect size; for the WISCI, the wearable robot had the largest effect size; and for balance, the end effector had the largest effect size. Among existing studies, none compared the effects of the three types of robots simultaneously; however, studies comparing the Lokomat and wearable robots have shown that wearable robots show greater improvement in walking speed [10]. In previous studies, the difference has been explained between wearable robots and stationary treadmill systems, such as the Lokomat, because the former is an overground walking system that requires patients to exert greater effort on their trunk and arms while engaging in higher cognitive and cardiovascular efforts [45]. This increased effort results in elevated muscle activity in the torso and pelvic floor [46], significantly enhancing motor and sensory functions [47]. Additionally, wearable robots provide more proprioceptive stimulation and adaptability to real-world environments through overground walking programs, thereby promoting greater neuroplasticity and facilitating connectivity remodulation [48]. The findings suggest that caution is needed in generalizing the efficacy of end-effector robots in improving balance, owing to limited studies. However, unlike exoskeleton-type robots, end-effector robots allow the knee and hip joints of participants to move freely, while their feet remain attached to the robot’s footplates. Previous studies have shown that this unrestricted movement of the hip and knee joints encourages destabilization training and promotes the coordination of postural control through feedback and feed-forward mechanisms, ultimately improving overall postural control [49].

Typically, approximately half of the recovery occurs within the initial 2 months following an injury, with a declining recovery rate over the subsequent 4 months. According to the 1-year mark post-injury, neurological recovery is generally close to completion [50]. Engaging in repetitive functional gait training during the acute phase aids in restoring muscle activation and relearning proper gait patterns. However, individuals with chronic SCI face challenges due to a slower rate of neuroplasticity, making motor relearning and reducing dependence on walking aids more challenging. The sub-analysis results of this study can also be said to support the above hypothesis because there was a significant improvement in the activities of daily living and WISCI in subacute patients with an onset period of 4–12 months. However, in this analysis, RAGT was more effective in the subacute phase than in the acute phase because, firstly, in the acute phase, there is a lack of medical stability and a higher complication rate [51], which may reduce the effectiveness of RAGT, which is a high-intensity repetitive exercise, and, secondly, because of the difference in treatment duration between the two groups. Previous subgroup analyses have shown that RAGT is more effective when the treatment duration is 2 months or more, but 71.4% of the trials in the acute phase had a treatment duration of less than 1 month, and only 25% of the trials in the subacute phase had a treatment duration of less than 1 month, which may explain the smaller effect analyzed in the acute phase. Future studies comparing treatment effects in groups of patients with the same treatment duration and protocol but different onset times are needed.

Strengths and limitations

The strength of this meta-analysis is that it provided the most up-to-date and comprehensive information on the efficacy of RAGT in individuals with SCI. Additionally, we sub-analyzed the effects of robot type, duration of intervention, and onset of SCI.

This meta-analysis has several limitations. First, there was a limited pool of involved articles, with the majority having small sample sizes. The included papers varied according to robot type: 16 Lokomat papers, 6 wearable robot papers, and 1 end-effector robot paper. The largest sample size of the included papers was 88, and the remaining papers all had small sample sizes of less than 100. Previous research has shown that pilot studies or studies with small sample sizes can inflate pooled effect sizes, even in meta-analyses [52], so this study should be interpreted with this in mind. Second, heterogeneity was observed among the included studies. For the primary outcome, the 10MWT speed meta-analysis was highly heterogeneous, with an I² value of 73.44%. This was because the study protocols varied according to robot type, intervention duration, treatment time, robot body weight support percentage, guidance force, and speed, and the injury level, severity, and onset time of the included patients varied. To address this heterogeneity, we performed subgroup analyses based on the duration of intervention and onset. Third, it does not take into account initial ASIA assessment results, level of injury, and patient age. Studies have shown that recovery and ambulation in SCI patients are associated with initial ASIA assessment results and age, and the applicability of RAGT varies depending on whether the patient is a paraplegia or tetraplegia [53]. However, none of the RCTs published to date compared patients according to ASIA grades and level of injury, so a meta-analysis could not be performed. Further studies are needed to address this issue.

CONCLUSION

The meta-analysis findings indicated that RAGT resulted in beneficial enhancements in the activities of daily living, muscular strength, and walking ability. Notably, these improvements were more prominent in interventions lasting >2 months and among subacute patients. Consequently, RAGT appears to be a viable option for individuals with SCI, with positive outcomes without significant adverse events.

Notes

CONFLICTS OF INTEREST

No potential conflict of interest relevant to this article was reported.

FUNDING INFORMATION

This study was supported by the Special Research Fund for ARM Development of the Korean Academy of Rehabilitation Medicine in 2023.

AUTHOR CONTRIBUTION

Conceptualization: Park JM, Shin JC. Methodology: Park JM. Formal analysis: Park JM. Funding acquisition: Shin JC. Project administration: Park JM. Visualization: Park JM. Writing – original draft: Park JM. Writing – review and editing: Park JM, Kim YW, Lee SJ, Shin JC. Approval of final manuscript: all authors.

SUPPLEMENTARY MATERIALS

Supplementary materials can be found via https://doi.org/10.5535/arm.230039.

Supplementary Material S1.

PRISMA 2020 Checklist

arm-230039-Supplementary-Table-1.pdf

Supplementary Material S2.

Search strategy

arm-230039-Supplementary-Table-2.pdf

Supplementary Fig. S1.

Funnel plot to detect publication bias. WISCI, walking index for spinal cord injury; 10MWT, 10 meter walk test; 6MWT, 6 min walk test; FEV1, forced expiratory volume in first second; FVC, forced vital capacity; PCF, peak cough flow; SMD, standardized mean difference.

arm-230039-Supplementary-Fig-1.pdf

Supplementary Fig. S2.

Subgroup analysis.

(A) Subgroup analysis of the effects of activities of daily living according to intervention period. (B) Subgroup analysis of the effects of activities of daily living according to onset period. (C) Subgroup analysis of the effects of muscular strength according to intervention period. (D) Subgroup analysis of the effects of muscular strength according to onset period. (E) Subgroup analysis of the effects of WISCI (walking index for spinal cord injury) according to intervention period. (F) Subgroup analysis of the effects of WISCI (walking index for spinal cord injury) according to onset period. (G) Subgroup analysis of the effects of 10MWT (10 meter walk test) speed according to intervention period. (H) Subgroup analysis of the effects of 10MWT (10 meter walk test) speed according to onset period. (I) Subgroup analysis of the effects of 6MWT (6 min walk test) distance according to intervention period. (J) Subgroup analysis of the effects of 6MWT (6 min walk test) distance according to onset period.

arm-230039-Supplementary-Fig-2.pdf

References

1. Mehrholz J, Kugler J, Pohl M. Locomotor training for walking after spinal cord injury. Cochrane Database Syst Rev 2012;11:CD006676.

2. Edgerton VR, Kim SJ, Ichiyama RM, Gerasimenko YP, Roy RR. Rehabilitative therapies after spinal cord injury. J Neurotrauma 2006;23:560–70.

3. Lünenburger L, Colombo G, Riener R, Dietz V. Biofeedback in gait training with the robotic orthosis Lokomat. Conf Proc IEEE Eng Med Biol Soc 2004;2004:4888–91.

4. Tan K, Koyama S, Sakurai H, Teranishi T, Kanada Y, Tanabe S. Wearable robotic exoskeleton for gait reconstruction in patients with spinal cord injury: a literature review. J Orthop Translat 2021;28:55–64.

5. Rodríguez-Fernández A, Lobo-Prat J, Font-Llagunes JM. Systematic review on wearable lower-limb exoskeletons for gait training in neuromuscular impairments. J Neuroeng Rehabil 2021;18:22.

6. Shin JC, Jeon HR, Kim D, Cho SI, Min WK, Lee JS, et al. Effects on the motor function, proprioception, balance, and gait ability of the end-effector robot-assisted gait training for spinal cord injury patients. Brain Sci 2021;11:1281.

7. Hesse S, Waldner A, Tomelleri C. Innovative gait robot for the repetitive practice of floor walking and stair climbing up and down in stroke patients. J Neuroeng Rehabil 2010;7:30.

8. National Evidence-based Healthcare Collaborating Agency (NECA). Gait therapy using lower limb rehabilitation robots in spinal cord injury patients NECA; 2021. p. 1–12.

9. Li R, Ding M, Wang J, Pan H, Sun X, Huang L, et al. Effectiveness of robotic-assisted gait training on cardiopulmonary fitness and exercise capacity for incomplete spinal cord injury: a systematic review and meta-analysis of randomized controlled trials. Clin Rehabil 2023;37:312–29.

10. Zhang L, Lin F, Sun L, Chen C. Comparison of efficacy of Lokomat and wearable exoskeleton-assisted gait training in people with spinal cord injury: a systematic review and network meta-analysis. Front Neurol 2022;13:772660.

11. Wardhana DPW, Maliawan S, Mahadewa TGB, Rosyidi RM, Wiranata S. The impact of machine learning and robot-assisted gait training on spinal cord injury: a systematic review and meta-analysis. J Clin Med 2023;12:7230.

12. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Syst Rev 2021;10:89.

13. Sterne JAC, Savović J, Page MJ, Elbers RG, Blencowe NS, Boutron I, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ 2019;366:l4898.

14. Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ 2008;336:924–6.

15. Thompson SG, Sharp SJ. Explaining heterogeneity in meta-analysis: a comparison of methods. Stat Med 1999;18:2693–708.

16. Fu R, Gartlehner G, Grant M, Shamliyan T, Sedrakyan A, Wilt TJ, et al. Conducting quantitative synthesis when comparing medical interventions: AHRQ and the Effective Health Care Program. J Clin Epidemiol 2011;64:1187–97.

17. Sterne JA, Egger M, Moher D. Addressing reporting biases. In : Higgins JPT, Green S, eds. Cochrane handbook for systematic reviews of interventions: Cochrane book series The Cochrane Collaboration; 2008. p. 297–333.

18. Chang SH, Afzal T, ; TIRR SCI Clinical Exoskeleton Group, Berliner J, Francisco GE. Exoskeleton-assisted gait training to improve gait in individuals with spinal cord injury: a pilot randomized study. Pilot Feasibility Stud 2018;4:62.

19. Yıldırım MA, Öneş K, Gökşenoğlu G. Early term effects of robotic assisted gait training on ambulation and functional capacity in patients with spinal cord injury. Turk J Med Sci 2019;49:838–43.

20. Ma TT, Zhang Q, Zhou TT, Zhang YQ, He Y, Li SJ, et al. Effects of robotic-assisted gait training on motor function and walking ability in children with thoracolumbar incomplete spinal cord injury. NeuroRehabilitation 2022;51:499–508.

21. Shin JC, Jeon HR, Kim D, Min WK, Lee JS, Cho SI, et al. Effects of end-effector robot-assisted gait training on gait ability, muscle strength, and balance in patients with spinal cord injury. NeuroRehabilitation 2023;53:335–46.

22. Song MS, Kang TW, Noh HJ, Bang DH. Effects of robot-assist training using virtual reality program on gait ability in patient with acute spinal cord injury. J Spec Educ Rehabil Sci 2012;51:347–62.

23. Piira A, Lannem AM, Sørensen M, Glott T, Knutsen R, Jørgensen L, et al. Robot-assisted locomotor training did not improve walking function in patients with chronic incomplete spinal cord injury: a randomized clinical trial. J Rehabil Med 2019;51:385–9.

24. Shin JC, Kim JY, Park HK, Kim NY. Effect of robotic-assisted gait training in patients with incomplete spinal cord injury. Ann Rehabil Med 2014;38:719–25.

25. Tang Q, Huang Q, Hu C. Research on design theory and compliant control for underactuated lower-extremity rehabilitation robotic systems code: (51175368); 2012.01-2015.12. J Phys Ther Sci 2014;26:1597–9.

26. Cheung EYY, Yu KKK, Kwan RLC, Ng CKM, Chau RMW, Cheing GLY. Effect of EMG-biofeedback robotic-assisted body weight supported treadmill training on walking ability and cardiopulmonary function on people with subacute spinal cord injuries - a randomized controlled trial. BMC Neurol 2019;19:140.

27. Labruyère R, van Hedel HJ. Strength training versus robot-assisted gait training after incomplete spinal cord injury: a randomized pilot study in patients depending on walking assistance. J Neuroeng Rehabil 2014;11:4.

28. Evans RW, Shackleton CL, West S, Derman W, Laurie Rauch HG, Baalbergen E, et al. Robotic locomotor training leads to cardiovascular changes in individuals with incomplete spinal cord injury over a 24-week rehabilitation period: a randomized controlled pilot study. Arch Phys Med Rehabil 2021;102:1447–56.

29. Shackleton C, Evans R, West S, Derman W, Albertus Y. Robotic walking to mitigate bone mineral density decline and adverse body composition in individuals with incomplete spinal cord injury: a pilot randomized clinical trial. Am J Phys Med Rehabil 2022;101:931–6.

30. Xiang XN, Zong HY, Ou Y, Yu X, Cheng H, Du CP, et al. Exoskeleton-assisted walking improves pulmonary function and walking parameters among individuals with spinal cord injury: a randomized controlled pilot study. J Neuroeng Rehabil 2021;18:86.

31. Gorman PH, Scott W, York H, Theyagaraj M, Price-Miller N, McQuaid J, et al. Robotically assisted treadmill exercise training for improving peak fitness in chronic motor incomplete spinal cord injury: a randomized controlled trial. J Spinal Cord Med 2016;39:32–44.

32. Wirz M, Mach O, Maier D, Benito-Penalva J, Taylor J, Esclarin A, et al. Effectiveness of automated locomotor training in patients with acute incomplete spinal cord injury: a randomized, controlled, multicenter trial. J Neurotrauma 2017;34:1891–6.

33. Edwards DJ, Forrest G, Cortes M, Weightman MM, Sadowsky C, Chang SH, et al. Walking improvement in chronic incomplete spinal cord injury with exoskeleton robotic training (WISE): a randomized controlled trial. Spinal Cord 2022;60:522–32.

34. Gil-Agudo Á, Megía-García Á, Pons JL, Sinovas-Alonso I, Comino-Suárez N, Lozano-Berrio V, et al. Exoskeleton-based training improves walking independence in incomplete spinal cord injury patients: results from a randomized controlled trial. J Neuroeng Rehabil 2023;20:36. Erratum in: J Neuroeng Rehabil 2023;20:160.

35. Alcobendas-Maestro M, Esclarín-Ruz A, Casado-López A, Muñoz-González I, Pérez-Mateos G, González-Valdizán E, et al. Lokomat robotic-assisted versus overground training within 3 to 6 months of incomplete spinal cord lesion: randomized controlled trial. Neurorehabil Neural Repair 2012;26:1058–63.

36. Duffell LD, Brown GL, Mirbagheri MM. Interventions to Reduce Spasticity and Improve Function in People With Chronic Incomplete Spinal Cord Injury: Distinctions Revealed by Different Analytical Methods. Neurorehabil Neural Repair 2015;29:566–76.

37. Esclarín-Ruz A, Alcobendas-Maestro M, Casado-Lopez R, Perez-Mateos G, Florido-Sanchez MA, Gonzalez-Valdizan E. A comparison of robotic walking therapy and conventional walking therapy in individuals with upper versus lower motor neuron lesions: a randomized controlled trial. Arch Phys Med Rehabil 2014;95:1023–31.

38. Field-Fote EC, Roach KE. Influence of a locomotor training approach on walking speed and distance in people with chronic spinal cord injury: a randomized clinical trial. Phys Ther 2011;91:48–60.

39. Mıdık M, Paker N, Buğdaycı D, Mıdık AC. Effects of robot-assisted gait training on lower extremity strength, functional independence, and walking function in men with incomplete traumatic spinal cord injury. Turk J Phys Med Rehabil 2020;66:54–9.

40. Nooijen CF, Ter Hoeve N, Field-Fote EC. Gait quality is improved by locomotor training in individuals with SCI regardless of training approach. J Neuroeng Rehabil 2009;6:36.

41. Hubli M, Dietz V. The physiological basis of neurorehabilitation--locomotor training after spinal cord injury. J Neuroeng Rehabil 2013;10:5.

42. Calancie B, Needham-Shropshire B, Jacobs P, Willer K, Zych G, Green BA. Involuntary stepping after chronic spinal cord injury. Evidence for a central rhythm generator for locomotion in man. Brain 1994;117(Pt 5):1143–59.

43. Scivoletto G, Ivanenko Y, Morganti B, Grasso R, Zago M, Lacquaniti F, et al. Plasticity of spinal centers in spinal cord injury patients: new concepts for gait evaluation and training. Neurorehabil Neural Repair 2007;21:358–65.

44. Winchester P, McColl R, Querry R, Foreman N, Mosby J, Tansey K, et al. Changes in supraspinal activation patterns following robotic locomotor therapy in motor-incomplete spinal cord injury. Neurorehabil Neural Repair 2005;19:313–24.

45. Corbianco S, Cavallini G, Dini M, Franzoni F, D’Avino C, Gerini A, et al. Energy cost and psychological impact of robotic-assisted gait training in people with spinal cord injury: effect of two different types of devices. Neurol Sci 2021;42:3357–66.

46. Chisholm AE, Alamro RA, Williams AM, Lam T. Overground vs. treadmill-based robotic gait training to improve seated balance in people with motor-complete spinal cord injury: a case report. J Neuroeng Rehabil 2017;14:27.

47. Khan AS, Livingstone DC, Hurd CL, Duchcherer J, Misiaszek JE, Gorassini MA, et al. Retraining walking over ground in a powered exoskeleton after spinal cord injury: a prospective cohort study to examine functional gains and neuroplasticity. J Neuroeng Rehabil 2019;16:145.

48. Brown AR, Martinez M. From cortex to cord: motor circuit plasticity after spinal cord injury. Neural Regen Res 2019;14:2054–62.

49. Gandolfi M, Valè N, Dimitrova E, Zanolin ME, Mattiuz N, Battistuzzi E, et al. Robot-assisted stair climbing training on postural control and sensory integration processes in chronic post-stroke patients: a randomized controlled clinical trial. Front Neurosci 2019;13:1143.

50. Piepmeier JM, Jenkins NR. Late neurological changes following traumatic spinal cord injury. J Neurosurg 1988;69:399–402.

51. Burns AS, Marino RJ, Kalsi-Ryan S, Middleton JW, Tetreault LA, Dettori JR, et al. Type and timing of rehabilitation following acute and subacute spinal cord injury: a systematic review. Global Spine J 2017;7(3 Suppl):175S–94S.

52. Beets MW, Weaver RG, Ioannidis JPA, Pfledderer CD, Jones A, von Klinggraeff L, et al. Influence of pilot and small trials in meta-analyses of behavioral interventions: a meta-epidemiological study. Syst Rev 2023;12:21.

53. Burns SP, Golding DG, Rolle WA Jr, Graziani V, Ditunno JF Jr. Recovery of ambulation in motor-incomplete tetraplegia. Arch Phys Med Rehabil 1997;78:1169–72.

Article information Continued

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Table 1.

Characteristics of the included studies

Study	No. of participants (experimental/control)	Age, years² (experimental/control)	ASIA grade (experimental/control)	Onset duration (experimental/control) (day)	Tetraplegia/paraplegia (experimental/control)	Initial WISCI (experimental/control)	Intervention protocol	Control protocol	Outcome measure	Main findings
Treadmill training exoskeleton robot-Lokomat
Alcobendas-Maestro et al., 2012 [35]	37/38	45.2±15.5/49.5±12.8	C 68/71	117.4±43.3/136.3±64.9	Tetraplegia 59/61	5.1±3.8/4.1±2.8	-Lokomat 30-min	Standard physical treatment	1. Speed (m/s)	No significant differences were found at entry between treatment groups
			D 32/29		Paraplegia 41/39		40 sessions (8 wk)	40 walking training	2. WISCI II	The WISCI II for the Lokomat group (16 [8.5–19]) was better than that for overground therapy (9 [8–16])
							-Body weight support was initially set at 60% of each individual’s weight and then decreased in accordance with load tolerance, but not <25% support	sessions of 1 h duration (8 wk)	3. Walk distance (m)	The 6MWT and LEMS displayed significant differences in favor of Lokomat therapy, but were not corrected for multiple comparisons
									4. FIM-Locomotor
									5. LEMS
									6. Ashworth
									7. VAS
Cheung et al., 2019 [26]	8/8	55.6±4.9/53.0±12.9	C 7/4	510.0±210.3/312.0±189.3	Tetraplegia 8/8	14.6±4.3/17.0±2.8	-Lokomat 30-min	Standard physical treatment	1. Speed (cm/s)	The Lokomat group improved walking ability and cardiopulmonary function in patients with SCI
			D 1/4				24 sessions (3 times per week for 8 weeks)	30-min	2. WISCI II	However, there were no significant differences in the control group
							-Body weight support was set at 40% of body weight to minimize individual difference	24 sessions (3 times per week for 8 weeks)	3. SCIM III
									4. LEMS
									5. Maximal oxygen consumption (L/kg/min)
									6. PEF (L/s)
									7. FEV1 (L)
									8. FVC (L)
Duffell et al., 2015 [36]	27/29	46.6±12.6/47.8±13.1	C N/R	3394.5±3942.0/2956.5±2956.5	N/R	14.7±5.2/13.8±5.8	-Lokomat 30–45 min	Standard physical treatment	1. Speed (m/s)	Walking speed and endurance improved, with no difference between interventions
			D N/R				12 sessions (3 times per week for 4 weeks)		2. Distance (m)
									3. Time (s)
									4. WISCI II
									5. MAS
Esclarín-Ruz et al., 2014 [37]	21/21	43.6±12.0/44.9±7.0	C 14/16	125.6±65.2/140.3±45.5	Tetraplegia 16/16	5.9±4.5/4.9±4.1	-Lokomat 30-min	Standard physical treatment	1. 10MWT (m/s)	RAGT yielded better results in the 6MWT and LEMS in patients
			D 7/5		Paraplegia 5/5		40 sessions (8 wk)	30-min	2. 6MWT (m)
							-Body weight support was initially set at 60% of each individual’s weight and then decreased in accordance with load tolerance, but not <25% support	40 sessions (8 wk)	3. FIM-Locomotor
									4. LEMS
Field-Fote and Roach, 2011 [38]	14/17	45.0±8.0/42.2±15.7	N/R	>365	N/R	LEMS	- Lokomat	Standard physical treatment	1. Speed (m/s)	In chronic motor incomplete SCI, there were no significant between-group differences
						12.7±6.9/12.9±5.3	60 sessions (12 wk)	Manual assistance for stepping	2. Distance walked (m)
							-Guidance forces were set at		3. LEMS
							100% to provide maximal assistance throughout the step cycle
Gorman et al., 2016 [31]	12/6	51.5±12.7/52.0±15.4	C 2/0	>365	Tetraplegia 8/6	LEMS	-Lokomat 25–45-min	Standard physical treatment	1. Body mass (kg)	Robot group improved peak VO2 than control group
			D 10/6		Paraplegia 4/0	34.2±11.5/36.2±8.4	36 sessions (12 wk)		2. Tissue fat (%)
							-Ultimately, partial		3. Lean tissue (kg)
							body weight support was set between 70%–80% if the participant was able to support his or her weight		4. Bone mineral content (kg)
									5. VO2 peak (ml/kg/min)
Labruyère and van Hedel, 2014 [27]	9/9	59±11	N/R	1500.0±1680.0	Tetraplegia 6	14.0±3.0	-Lokomat 45 min	Strength training	1. 10MWT (m/s)	Chronic incomplete SCI dependent on walking assistance, robot group was not more effective in improving walking-related outcome compared to lower extremity strength training
					Paraplegia 3		16 sessions (4wk)	45-min	2. WISCI
							-30% bodyweight support and a speed of 1–2 km/h	16 sessions (4 wk)	3. SCIM
									4. BBS
									5. LEMS
									6. Figure eight test
									7. Gait symmetry
									8. PCI
									9. BBS
Ma et al., 2022 [20]	10/10	8.4±1.1/8.6±1.2	N/R	400.8±147.0/468.0±158.1	N/R	16.2±1.3/15.9±2.2	-Lokomat 30-min	Standard physical treatment	1. 10MWT (m/s)	RAGT may significantly improve the immediate motor function and walking ability of children with thoracolumbar incomplete SCI
							40 sessions (8 wk)	60-min	2. 6MWT (m)
							-70%–40% bodyweight support	40 sessions (8 wk)	3. LEMS
									4. PCI
									5. WISCI
									6. Centre of pressure (cm²)
Mıdık et al., 2020 [39]	15/15	35.4±12.1/37.9±10.0	C 6/10	411.4±637.9/861.6±662.5	Tetraplegia 0/0	9.8±1.4/11.0±1.1	-Lokomat 30-min	Standard physical treatment	1. WISCI	Conventional rehabilitation is useful in terms of the improvement in the lower extremity motor function, walking, and functional status in men with incomplete SCI. Additional RAGT provides a better improvement in the lower extremity motor function and functional independence
			D 9/5		Paraplegia 15/15		15 sessions (5 wk)	30-min	2. SCIM
							-In addition to standard physical treatment	25 sessions (5 wk)	3. LEMS
							-50% bodyweight support and a speed of 1.5 km/h
Nooijen et al., 2009 [40]	12/13	44.3±8.9/38.2±14.6	N/R	3327.5±3214.8/1569.2±1545.4	Tetraplegia 0/11	N/R	-Lokomat 60-min	Standard physical treatment	1. Cadence (steps/min)	No significant differences were found among training groups; however, there was an interaction effect, indicating that step and stride length improved least in the robot-assisted gait training group
					Paraplegia 15/2		60 sessions (12 wk)	60-min	2. Symmetry index (%)
							-30% bodyweight support	60 sessions (12 wk)	3. Step length (m)
									4. Stride length (m)
									5. Intralimb coordination
									6. Timing of onset knee
Piira et al., 2019 [23]	7/12	55.0±8.0/46.0±15.0	C 1/5	7665.0±839.0/5475.0±6570.0	Tetraplegia 4/6	LEMS	-Lokomat 20–30 min	Standard physical treatment	1. 10MWT (m/s)	In chronic SCI, robot-assisted gait training did not restore independent walking function
			D 6/7		Paraplegia 3/6	26.6±22.0/27.8±31.9	60 sessions (24 wk)	60 sessions (24 wk)	2. 6MWT (m)	A modest, but non-significant, effect was seen on muscle strength and balance
							-<40% bodyweight support		3. LEMS
									4. BBS
									5. Modified functional reach test
Shin et al., 2014 [24]	27/26	43.2±14.4/48.2±11.5	N/R	99.9±90.6/81.9±59.1	Tetraplegia 15/16	5.9±10.9/6.9±12.6	-Lokomat 40-min	Standard physical treatment	1. WISCI	RAGT combined with conventional physiotherapy could yield more improvement in ambulatory function than conventional therapy alone
					Paraplegia 12/10		12 sessions (4 wk)	30-min	2. SCIM
							-In addition to standard physical treatment	40 sessions (4 wk)	3. LEMS
							-50% bodyweight support and a speed of 1.5 km/h		4. Ambulatory motor index (AMI)
Tang et al., 2014 [25]	15/15	38.1±7.1/39.2±8.1	D 15/15	Median 189	Tetraplegia 0/0	N/R	-Lokomat	40 min 1 session	1. 10MWT (m/s)	RAGT not only decreased reaction time, but also improved the walking ability
					Paraplegia 15/15		40 min 1 session	Ergo_bike rate of 45 rpm with a work load of 60 W	2. Probe reaction time
							-35%–70% bodyweight support and a speed of 1.5–1.8 km/h
Wirz et al., 2017 [32]	9/9	35.56±13.8/34.3±16.0	B 3/6	35.1±18.6/43.2±25.7	Tetraplegia 7/6	N/R	-Lokomat 50-min	Standard physical treatment	1. SCIM	No significant differences were found among training groups
			C 6/3		Paraplegia 2/3		34 sessions (8 wk)	25-min	2. Spasticity (MAS)
							-Speed of 1.6–3.5 km/h	34 sessions (8 wk)

Yıldırım et al., 2019 [19]	44/44	32±5.2/36.5±5.5	A 21/18	90±13.7/90±13.7	Tetraplegia 9/7	5.0±6.9/5.0±5.1	-Lokomat 30-min	Standard physical treatment	1. WISCI	RAGT combined with conventional therapy was found to be superior to the conventional therapy in terms of gait function and level of disability
			BCD 23/26		Paraplegia 35/37		16 sessions (8 wk)	30-min	2. FIM
							-Standard physical treatment	40 sessions (twice a day)
							30-min 40 sessions (twice a day) (8 weeks)	(8 wk)
Song et al., 2012 [22]	11/11	53.7±8.8/53.3±6.0	N/R	20.2±5.0/20±4.8	Tetraplegia 9/10	N/R	-Lokomat 20-min	Standard physical treatment	1. Balance (TETRAX fall risk)	RAGT significantly improved in walking ability and lower fall risk
					Paraplegia 2/1		20 sessions (4 wk)	20-min	2. 10MWT (m/s)
							-Standard physical treatment	20 sessions (4 wk)	3. 6MWT (m)
							20-min		4. MBI
							20 sessions (4 wk)
Wearable gait robot-Ekso, HANK, AIDER
Chang et al., 2018 [18]	4/3	56.0±17.0/60.0±2.0	C 1/1	5475.0±5110.0/2555.0±1095.0	Tetraplegia 2/1	N/R	-Ekso 60-min	Standard physical treatment	1. 10MWT (m/s)	RAGT could be applied to individuals with incomplete SCI to facilitate gait recovery
			D 3/2		Paraplegia 2/2		15 sessions (3 wk)	60-min	2. 6MWT (m)
								15 sessions (3 wk)	3. TUG (s)
									4. Step length (m)
Edwards et al., 2022 [33]	9/10	41.7±8.5/51.9±14.5	C 6/3	3066.0±3134.2/2568.3±1594.1	Tetraplegia 7/8	12.1±4.4/13.8±4.5	-Ekso GT 45-min	Body weight support	1. Gait speed (m/s)	RAGT not statistically significant in gait speed
			D 3/7		Paraplegia 2/2		36 sessions (12 wk)	treadmill training
								45-min
								36 sessions (12 wk)
Evans et al., 2021 [28]	8/8	41.0±11.0/38.0±14.0	C 4/5	4745.0±2920.0/2555.0±2190.0	Tetraplegia 8/8	N/R	-Ekso GT 60-min	60-min 72 sessions (24 wk)	1. Heart rate	Cardiovascular efficiency of exoskeleton walking improved, particularly over the first 6 weeks
			D 4/3		Paraplegia 0/0		72 sessions (24 wk)	Warm-up and mobility (5 min)	2. Heart rate variability
								Resistance training (20–30 min)	3. Systolic blood pressure (mmHg)
								Cardiovascular training (20–30 min)	4. Diastolic blood pressure (mmHg)
									5. Ankle brachial pressure index (ABPI)
									6. Distance (m)
									7. Rating of perceived exertion (Borg)
Gil-Agudo et al., 2023 [34]	11/10	41.0±12.4/51.8±11.9	C 8/4	144.6±39/166.5±69	Tetraplegia 4/2	11.9±4.3/11.7±3.8	-HANK 30-min	Standard physical treatment	1. LEMS	Exoskeleton improved their walking independence as measured by the WISCI-II after the treatment
			D 3/6		Paraplegia 7/8		15 sessions (5 wk)	30-min	2. 10MWT (m/s)
								15 sessions (5 wk)	3. TUG (s)
									4. 6MWT (m)
									5. WISCI
									6. SCIM
Shackleton et al., 2022 [29]	8/8	40.5±11.2/38.4±14.3	C 4/5	5037.0±3029.5/2664.5±2336.0	Tetraplegia 8/8	N/R	-Ekso Bionics 60-min	Standard physical treatment	1.Bone mineral density (g/cm²)	Twenty-four weeks of robot locomotor training is possibly a sufficient duration to prevent the progressive decline of bone mineral density
			D 4/3		Paraplegia 0/0		72 sessions (24 wk)	60-min	2. Fat mass (kg, %)
								72 sessions (24 wk)	3. Fat-free soft tissue mass (kg)
Xiang et al., 2021 [30]	9/9	39.8±12.2/36.6±11.8	A 8/4	60.0±118.5/60.0±13.1	Tetraplegia 5/4	N/R	-AIDER 60-min	Standard physical treatment	1. FVC (L)	Exoskeleton-assisted walking has potential benefits to facilitate pulmonary function parameters among individuals with lower thoracic neurological level of SCI compared with conventional therapy
			B 0/3		Paraplegia 4/5		16 sessions (4 wk)	60-min	2. FEV1 (L)
			C 1/3				-40%–60% maximal heart rate	16 sessions (4 wk)	3. PEF (L/s)
									4. Maximal voluntary ventilation (MVV) (L)
									5. Distance (m)
									6. Heart rate
									7. Rating of Perceived Exertion
									8. SpO2
									9. LEMS
End effector gait robot-Morning walk
Shin et al., 2023 [21]	16/13	49.5±27.0/59.6±7.5	C 2/4	61.7±44.9/58.2±50.7	Tetraplegia 14/10	WISCI II	-Morning walk 30-min	Standard physical treatment	1. WISCI	End-effector robot gait training could improve balance and gait abilities substantially better than conventional therapy
			D 14/9		Paraplegia 2/2	3.6±4.6/3.7±6.6	20 sessions (4 wk)	90-min	2. SCIM
							-20% body weight support	20 sessions (4 wk)	3. LEMS
							-Standard physical treatment 60-min		4. Proprioception
							20 sessions (4 wk)		5. BBS
									6. WISCI II
									7. SCIM III

ASIA, American Spinal Injury Association; WISCI, walking index for spinal cord injury; N/R, not recorded; LEMS, lower extremity motor score; FIM, functional independence measure; VAS, visual analogue scale; SCIM, spinal cord independence measurement; PEF, peak expiratory flow; FEV1, forced expiratory volume in the first second; MAS, modified Ashworth scale; 10MWT, 10 meter walk test; 6MWT, 6 min walk test; BBS, Berg balance scale; PCI, Physiological Cost Index; TETRAX, Tetrax (Sunlight Medical Ltd.); MBI, modified Barthel index; TUG, Timed Up and Go Test; FVC, forced vital capacity; RAGT, robotic-assisted gait training.

Outcome measure		Summary of findings		Heterogeneity	Publication bias	Quality of evidence assessment (GRADE)
Outcome measure		No. of patients Experimental/control (trials)	Effect size (95% confidence interval)	I² (%)	Egger’s test	Risk of bias^a)	Inconsistency^b)	Indirectness^c)	Imprecision^d)	Publication bias^e)	Quality of evidence^f)
Activities of daily living	FIM, SCIM, MBI	208/203 (11)	SMD 0.24 (0.04–0.43)^**	0	0.950	Not serious	Not serious	Not serious	Not serious	None	High
Muscular strength	LEMS	184/187 (12)	MD 0.23 (0.02–044)^**	0	0.592	Not serious	Not serious	Not serious	Not serious	None	High
Spasticity	MAS	73/75 (3)	MD -0.05 (-0.37 to 0.28)	0	0.952	Serious	Not serious	Not serious	Serious	None	Low
Balance	BBS	32/34 (3)	MD 0.44 (-0.18 to 1.06)	33.42	0.269	Not serious	Serious	Not serious	Serious	None	Low
Walking ability	WISCI	215/212 (10)	MD 0.31 (0.07–0.55)^**	30.67	0.260	Serious	Not serious	Not serious	Not serious	None	Moderate
	10MWT speed (m/s)	172/176 (13)	MD -0.02 (-0.46 to 0.42)	73.44	0.521	Serious	Very serious	Not serious	Serious	None	Very low
	6MWT distance (m)	134/134 (10)	MD 0.38 (0.14–0.63)^**	0	0.256	Serious	Not serious	Not serious	Not serious	None	Moderate
	Step length (m)	16/16 (2)	MD -0.15 (-0.84o 0.55)	0	N/A	Not serious	Not serious	Not serious	Serious	Suspected	Low
Body composition	Body mass (kg)	20/14 (2)	MD 0.02 (-0.67 to 0.71)	0	N/A	Not serious	Not serious	Not serious	Serious	None	Moderate
	Lean tissue (kg)	20/14 (2)	MD 0.02 (-0.67 to 0.72)	0	N/A	Not serious	Not serious	Not serious	Serious	None	Moderate
	Tissue fat (%)	20/14 (2)	MD 0.09 (-0.60 to 0.79)	0	N/A	Not serious	Not serious	Not serious	Serious	None	Moderate
Cardiopulmonary Function	FEV1 (L)	17/17 (2)	MD 0.49 (-0.20 to 1.18)	0	N/A	Not serious	Not serious	Not serious	Serious	None	Moderate
	Forced vital capacity (L)	17/17 (2)	MD 0.33 (-0.35 to 1.02)	0	N/A	Not serious	Not serious	Not serious	Serious	None	Moderate
	Heart rate (beats/min)	17/17 (2)	MD 0.56 (-0.71 to 1.30)	10.09	N/A	Not serious	Not serious	Not serious	Serious	None	Moderate
	Peak expiratory flow (L/s)	17/17 (2)	MD 0.26 (-0.41 to 0.94)	0	N/A	Not serious	Not serious	Not serious	Serious	Suspected	Low

Outcome measure		No. of patients Experimental/control (trials)	Effect size (95% confidence interval)	I² (%)
Activities of daily living	Intervention ≤1 month	89/84 (6)	SMD 0.10 (-0.20 to 0.40)	0
	Intervention >2 months	119/119 (5)	S MD 0.34 (0.09–0.60)^**	0
	Acute	107/103 (5)	SMD 0.19 (-0.09 to 0.46)	0
	Subacute	69/68 (3)	SMD 0.37 (0.03–0.70)^**	0
	Chronic	32/32 (3)	SMD 0.14 (-0.35 to 0.63)	0
Muscular strength	Intervention ≤1 month	87/82 (6)	MD 0.20 (-0.13 to 0.53)	12.97
	Intervention >2 months	76/76 (4)	MD 0.29 (-0.03 to 0.62)	0
	Intervention >3 months	21/29 (2)	MD 0.15 (-0.42 to 0.71)	0
	Acute	52/48 (3)	MD 0.00 (-0.39 to 0.3)	0
	Subacute	69/68 (3)	MD 0.26 (-0.07 to 0.60)	0
	Chronic	63/71 (3)	MD 0.38 (-0.02 to 0.78)	22.67
WISCI	Intervention ≤1 month	105/102 (6)	MD 0.37 (-0.11 to 0.84)	62.54
	Intervention >2 months	110/110 (4)	MD 0.33 (0.07–0.60)^**	0
	Acute	87/83 (3)	MD 0.35 (-0.09 to 0.78)	45.65
	Subacute	69/68 (3)	MD 0.51 (0.06–0.96)^**	35.72
	Chronic	59/61 (4)	MD 0.10 (-0.34 to 0.54)	26.96
10MWT speed (m/s)	Intervention ≤1 month	66/61 (6)	MD 0.12 (-0.24 to 0.48)	2.52
	Intervention >2 months	76/76 (4)	MD 0.19 (-0.13 to 0.51)	0
	Intervention >3 months	30/39 (3)	MD -0.70 (-2.60 to 1.20)	91.81
	Acute	31/27 (3)	MD 0.10 (-0.67 to 0.87)	47.35
	Subacute	84/83 (4)	MD 0.14 (-0.16 to 0.44)	0
	Chronic	57/66 (6)	MD -0.23 (-1.21 to 0.75)	84.61
6MWT distance (m)	Intervention ≤1 month	51/46 (5)	MD 0.59 (0.10–1.07)^**	23.92
	Intervention >2 months	68/68 (3)	MD 0.38 (0.04–0.72)^**	0
	Intervention >3 months	15/20 (2)	MD -0.04 (-0.72 to 0.64)	0
	Acute	40/36 (4)	MD 0.69 (0.06–1.32)^**	38.51
	Subacute	69/68 (3)	MD 0.31 (-0.02 to 0.65)	0
	Chronic	25/30 (3)	MD 0.26 (-0.35 to 0.86)	18.50