Efficacy of end-effector Robot-Assisted Gait Training in subacute stroke patients: Clinical and gait outcomes from a pilot bi-centre study

How robot-assisted gait training affects gait ability, balance and kinematic parameters after stroke: a systematic review and meta-analysis

INTRODUCTION

Gait ability is often cited by stroke survivors. Robot-assisted gait training (RAGT) can help stroke patients with lower limb motor impairment regain motor coordination.

EVIDENCE ACQUISITION

PubMed, Cochrane Library, Embase were systematically searched until September 2023, to identify randomized controlled trials presenting: stroke survivors as participants; RAGT as intervention; conventional rehabilitation as a comparator; gait assessment, through scales or quantitative parameters, as outcome measures.

EVIDENCE SYNTHESIS

Twenty-seven publications involving 1167 patients met the inclusion criteria. Meta-analysis showed no significant differences in speed, cadence, spatial symmetry, and changes in joint mobility angles between the RAGT group and the control group. In addition, RAGT was associated with changes in affected side step length (SMD=0.02, 95% CI: 0.01, 0.03; P<0.0001), temporal symmetry (SMD=-0.38, 95% CI: -0.6, -0.16; P=0.0006], Six-Minute Walk Test (SMD=25.14, 95% CI: 10.19, 40.09; P=0.0010] and Functional Ambulation Categories (SMD=0.32, 95% CI: 0.01, 0.63; P=0.04). According to the PEDro scale, 19 (70.4%) studies were of high quality and eight were of moderate quality (29.6%).

CONCLUSIONS

Taken together, the review synthesis showed that RAGT might have a potential role in the recovery of walking dysfunction after stroke. However, its superiority over conventional rehabilitation requires further research. Additionally, it may provide unexpected benefits that the effects of RAGT with different types or treatment protocols were further compared.

Brain-computer interface treatment for gait rehabilitation in stroke patients

The use of Brain-Computer Interfaces (BCI) as rehabilitation tools for chronically ill neurological patients has become more widespread. BCIs combined with other techniques allow the user to restore neurological function by inducing neuroplasticity through real-time detection of motor-imagery (MI) as patients perform therapy tasks. Twenty-five stroke patients with gait disability were recruited for this study. Participants performed 25 sessions with the MI-BCI and assessment visits to track functional changes during the therapy. The results of this study demonstrated a clinically significant increase in walking speed of 0.19 m/s, 95%CI [0.13-0.25], p < 0.001. Patients also reduced spasticity and improved their range of motion and muscle contraction. The BCI treatment was effective in promoting long-lasting functional improvements in the gait speed of chronic stroke survivors. Patients have more movements in the lower limb; therefore, they can walk better and safer. This functional improvement can be explained by improved neuroplasticity in the central nervous system.

Effect of exoskeleton robot-assisted training on gait function in chronic stroke survivors: a systematic review of randomised controlled trials

OBJECTIVES

Numbers of research have reported the usage of robot-assisted gait training for walking restoration post-stroke. However, no consistent conclusion has been reached yet about the efficacy of exoskeleton robot-assisted training (ERAT) on gait function of stroke survivors, especially during the chronic period. We conducted a systematic review to investigate the efficacy of ERAT on gait function for chronic stroke survivors.

DESIGN

This review followed the Participant, Intervention, Comparison and Outcome principle.

DATA SOURCES

PubMed, Cochrane Library, Web of Science, Embase and Cumulative Index to Nursing and Allied Health Literature databases were systematically searched until December 2022.

ELIGIBILITY CRITERIA

Only randomised controlled trials (RCTs) were included and these RCTs took patients who had a chronic stroke as participants, exoskeleton robot-assisted gait training as intervention, regular rehabilitation therapy as comparison and gait-related functional assessments as outcomes.

DATA EXTRACTION AND SYNTHESIS

Data extraction and synthesis used the reporting checklist for systematic review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The risk of bias and methodological quality of included studies were evaluated by two independent investigators under the guidance of Cochrane risk of bias.

RESULTS

Out of 278 studies, a total of 10 studies (n=323, mean age 57.6 years, 63.2% males) were identified in this systematic review. According to the Cochrane risk of bias, the quality of these studies was assessed as low risk. Six studies reported favourable effects of ERAT on gait function involving gait performance, balance function and physical endurance, and the ERAT group was significantly superior when compared with the control group. In contrast, the other four trials showed equal or negative effects of ERAT considering different study designs. All the included studies did not claim any serious adverse events.

CONCLUSION

ERAT could be an efficient intervention to improve gait function for individuals who had a chronic stroke. However, more rigorously designed trials are required to draw more solid evidence.

PROSPERO REGISTRATION NUMBER

CRD42023410796.

Comparative efficacy of gait training for balance outcomes in patients with stroke: A systematic review and network meta-analysis

Background

Growing evidence suggests that gait training can improve stroke patients’ balance outcomes. However, it remains unclear which type of gait training is more effective in improving certain types of balance outcomes in patients with stroke. Thus, this network meta-analysis (NMA) included six types of gait training (treadmill, body-weight-supported treadmill, virtual reality gait training, robotic-assisted gait training, overground walking training, and conventional gait training) and four types of balance outcomes (static steady-state balance, dynamic steady-state balance, proactive balance, and balance test batteries), aiming to compare the efficacy of different gait training on specific types of balance outcomes in stroke patients and determine the most effective gait training.

Method

We searched PubMed, Embase, Medline, Web of Science, and Cochrane Library databases from inception until 25 April 2022. Randomized controlled trials (RCTs) of gait training for the treatment of balance outcomes after stroke were included. RoB2 was used to assess the risk of bias in the included studies. Frequentist random-effects network meta-analysis (NMA) was used to evaluate the effect of gait training on four categories of balance outcomes.

Result

A total of 61 RCTs from 2,551 citations, encompassing 2,328 stroke patients, were included in this study. Pooled results showed that body-weight-support treadmill (SMD = 0.30, 95% CI [0.01, 0.58]) and treadmill (SMD = 0.25, 95% CI [0.00, 0.49]) could improve the dynamic steady-state balance. Virtual reality gait training (SMD = 0.41, 95% CI [0.10, 0.71]) and body-weight-supported treadmill (SMD = 0.41, 95% CI [0.02, 0.80]) demonstrated better effects in improving balance test batteries. However, none of included gait training showed a significant effect on static steady-state balance and proactive balance.

Conclusion

Gait training is an effective treatment for improving stroke patients’ dynamic steady-state balance and balance test batteries. However, gait training had no significant effect on static steady-state balance and proactive balance. To achieve maximum efficacy, clinicians should consider this evidence when recommending rehabilitation training to stroke patients. Considering body-weight-supported treadmill is not common for chronic stroke patients in clinical practice, the treadmill is recommended for those who want to improve dynamic steady-state balance, and virtual reality gait training is recommended for those who want to improve balance test batteries.

Limitation

Missing evidence in relation to some types of gait training is supposed to be taken into consideration. Moreover, we fail to assess reactive balance in this NMA since few included trials reported this outcome.

Systematic Review Registration

PROSPERO, identifier CRD42022349965.

Balance Rehabilitation through Robot-Assisted Gait Training in Post-Stroke Patients: A Systematic Review and Meta-Analysis

BACKGROUND

Balance impairment is a common disability in post-stroke survivors, leading to reduced mobility and increased fall risk. Robotic gait training (RAGT) is largely used, along with traditional training. There is, however, no strong evidence about RAGT superiority, especially on balance. This study aims to determine RAGT efficacy on balance of post-stroke survivors.

METHODS

PubMed, Cochrane Library, and PeDRO databases were investigated. Randomized clinical trials evaluating RAGT efficacy on post-stroke survivor balance with Berg Balance Scale (BBS) or Timed Up and Go test (TUG) were searched. Meta-regression analyses were performed, considering weekly sessions, single-session duration, and robotic device used.

RESULTS

A total of 18 trials have been included. BBS pre-post treatment mean difference is higher in RAGT-treated patients, with a pMD of 2.17 (95% CI 0.79; 3.55). TUG pre-post mean difference is in favor of RAGT, but not statistically, with a pMD of -0.62 (95%CI - 3.66; 2.43). Meta-regression analyses showed no relevant association, except for TUG and treatment duration (β = -1.019, 95% CI - 1.827; -0.210, p-value = 0.0135).

CONCLUSIONS

RAGT efficacy is equal to traditional therapy, while the combination of the two seems to lead to better outcomes than each individually performed. Robot-assisted balance training should be the focus of experimentation in the following years, given the great results in the first available trials. Given the massive heterogeneity of included patients, trials with more strict inclusion criteria (especially time from stroke) must be performed to finally define if and when RAGT is superior to traditional therapy.

Evidence-based improvement of gait in post-stroke patients following robot-assisted training: A systematic review

BACKGROUND

The recovery of walking after stroke is a priority goal for recovering autonomy. In the last years robotic systems employed for Robotic Assisted Gait Training (RAGT) were developed. However, literature and clinical practice did not offer standardized RAGT protocol or pattern of evaluation scales.

OBJECTIVE

This systematic review aimed to summarize the available evidence on the use of RAGT in post-stroke, following the CICERONE Consensus indications.

METHODS

The literature search was conducted on PubMed, Cochrane Library and PEDro, including studies with the following criteria: 1) adult post-stroke survivors with gait disability in acute/subacute/chronic phase; 2) RAGT as intervention; 3) any comparators; 4) outcome regarding impairment, activity, and participation; 5) both primary studies and reviews.

RESULTS

Sixty-one articles were selected. Data about characteristics of patients, level of disability, robotic devices used, RAGT protocols, outcome measures, and level of evidence were extracted.

CONCLUSION

It is possible to identify robotic devices that are more suitable for specific phase disease and level of disability, but we identified significant variability in dose and protocols. RAGT as an add-on treatment seemed to be prevalent. Further studies are needed to investigate the outcomes achieved as a function of RAGT doses delivered.

Human-Robot Cooperative Strength Training Based on Robust Admittance Control Strategy

A stroke is a common disease that can easily lead to lower limb motor dysfunction in the elderly. Stroke survivors can effectively train muscle strength through leg flexion and extension training. However, available lower limb rehabilitation robots ignore the knee soft tissue protection of the elderly in training. This paper proposes a human-robot cooperative lower limb active strength training based on a robust admittance control strategy. The stiffness change law of the admittance model is designed based on the biomechanics of knee joints, and it can guide the user to make force correctly and reduce the stress on the joint soft tissue. The controller will adjust the model stiffness in real-time according to the knee joint angle and then indirectly control the exertion force of users. This control strategy not only can avoid excessive compressive force on the joint soft tissue but also can enhance the stimulation of quadriceps femoris muscles. Moreover, a dual input robust control is proposed to improve the tracking performance under the disturbance caused by model uncertainty, interaction force and external noise. Experiments about the controller performance and the training feasibility were conducted with eight stroke survivors. Results show that the designed controller can effectively influence the interaction force; it can reduce the possibility of joint soft tissue injury. The robot also has a good tracking performance under disturbances. This control strategy also can enhance the stimulation of quadriceps femoris muscles, which is proved by measuring the muscle electrical signal and interaction force. Human-robot cooperative strength training is a feasible method for training lower limb muscles with the knee soft tissue protection mechanism.

RObotic-Assisted Rehabilitation for balance and gait in Stroke patients (ROAR-S): study protocol for a preliminary randomized controlled trial

Background

Stroke, the incidence of which increases with age, has a negative impact on motor and cognitive performance, quality of life, and the independence of the person and his or her family, leading to a number of direct and indirect costs. Motor recovery is essential, especially in elderly patients, to enable the patient to be independent in activities of daily living and to prevent falls. Several studies have shown how robotic training associated with physical therapy influenced functional and motor outcomes of walking after stroke by improving endurance and walking strategies.

Considering data from previous studies and patients’ needs in gait and balance control, we hypothesized that robot-assisted balance treatment associated with physical therapy may be more effective than usual therapy performed by a physical therapist in terms of improving static, dynamic balance and gait, on fatigue and cognitive performance.

Methods

This is an interventional, single-blinded, preliminary randomized control trial. Twenty-four patients of both sexes will be recruited, evaluated, and treated at the UOC Rehabilitation and Physical Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome from January to December 2022. Patients will be randomized into two groups: the experimental group will perform specific rehabilitation for balance disorder using the Hunova® robotic platform (Movendo Technology srl, Genoa, IT) for 3 times a week, for 4 weeks (12 total sessions), and for 45 min of treatment, in addition to conventional treatment, while the conventional group (GC) will perform only conventional treatment as per daily routine. All patients will undergo clinical and instrumental evaluation at the beginning and end of the 4 weeks of treatment.

Conclusions

The study aims to evaluate the improvement in balance, fatigue, quality of life, and motor and cognitive performance after combined conventional and robotic balance treatment with Hunova® (Movendo Technology srl, Genoa, IT) compared with conventional therapy alone. Robotic assessment to identify the most appropriate and individualized rehabilitation treatment may allow reducing disability and improving quality of life in the frail population. This would reduce direct and indirect social costs of care and treatment for the National Health Service and caregivers.

Trial registration

ClinicalTrials.gov NCT05280587. Registered on March 15, 2022.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06812-w.

Hybrid robot-assisted gait training for motor function in subacute stroke: a single-blind randomized controlled trial

Background

Robot-assisted gait training (RAGT) is a practical treatment that can complement conventional rehabilitation by providing high-intensity repetitive training for patients with stroke. RAGT systems are usually either of the end-effector or exoskeleton types. We developed a novel hybrid RAGT system that leverages the advantages of both types.

Objective

This single-blind randomized controlled trial evaluated the beneficial effects of the novel RAGT system both immediately after the intervention and at the 3-month follow-up in nonambulatory patients with subacute stroke.

Methods

We recruited 40 patients with subacute stroke who were equally randomized to receive conventional rehabilitation either alone or with the addition of 15 RAGT sessions. We assessed lower-extremity motor function, balance, and gait performance by using the following tools: active range of motion (AROM), manual muscle test (MMT), the Fugl–Meyer Assessment (FMA) lower-extremity subscale (FMA-LE) and total (FMA-total), Postural Assessment Scale for Stroke (PASS), Berg Balance Scale (BBS), Tinetti Performance-Oriented Mobility Assessment (POMA) balance and gait subscores, and the 3-m and 6-m walking speed and Timed Up and Go (TUG) tests. These measurements were performed before and after the intervention and at the 3-month follow-up.

Results

Both groups demonstrated significant within-group changes in the AROM, MMT, FMA-LE, FMA-total, PASS, BBS, POMA, TUG, and 3-m and 6-m walking speed tests before and after intervention and at the 3-month follow-up (p < 0.05). The RAGT group significantly outperformed the control group only in the FMA-LE (p = 0.014) and total (p = 0.002) assessments.

Conclusion

Although the novel hybrid RAGT is effective, strong evidence supporting its clinical effectiveness relative to controls in those with substantial leg dysfunction after stroke remains elusive.

Trial registration The study was registered with an International Standard Randomized Controlled Trial Number, ISRCTN, ISRCTN15088682. Registered retrospectively on September 16, 2016, at https://www.isrctn.com/ISRCTN15088682

Efficacy of Robot-Assisted Gait Training Combined with Robotic Balance Training in Subacute Stroke Patients: A Randomized Clinical Trial

Recently, the use of robotic technology in gait and balance rehabilitation of stroke patients has been introduced, with positive results. The purpose of this study was to evaluate the effectiveness of robotic gait and trunk rehabilitation compared to robotic gait training alone on balance, activities, and participation measures in patients with subacute stroke. The study was a randomized, controlled, single blind, parallel group clinical trial. Thirty-six patients with first ischemic or hemorrhagic stroke event were enrolled, and they were randomized in two groups: Gait Group (GG), where they received only robotic treatment for gait rehabilitation through an end-effector system, and Gait/Trunk Group (GTG) where they performed end-effector gait rehabilitation and balance with a robotic platform, 3 times/week for 12 sessions/month. At the end of the study, there was an improvement in balance ability in both groups. Instead, the lower limb muscle strength and muscle tone significantly improved only in the GTG group, where we found a significant reduction in the trunk oscillations and displacement during dynamic exercises more than the GG group. The robotic platform which was added to the gait robotic treatment offers more intense and controlled training of the trunk that positively influences the tone and strength of lower limb muscles.

Model Analysis and Experimental Study of Lower Limb Rehabilitation Training Device Based on Gravity Balance

More hemiplegia patients tend to use equipment for rehabilitation training due to the lack of physical therapists and the low effect of manual training. Nowadays, lower limb rehabilitation training devices for patients in grade 2 of the Medical Research Council (MRC-2) scale are still scarce and have some issues of poor autonomy and cannot relieve the muscle weakness of patients. To address these problems, a prototype based on gravity balance was designed with the combination of springs and linkages to enable patients to passively experience the rehabilitation training in the state of balancing the gravity of lower limbs. The motion of the mechanism was analyzed to obtain the functional relation between the motor rotation angle and the joints’ angle. Based on the principle of constant potential energy, a gravity balance mathematical model of the device was established, analyzed, and simulated. Moreover, through the training experiment, the results show that when subjects in three different weights were trained under the rehabilitation device with and without gravity balance, the required torques of the motor and EMG signal strength of the knee and hip joints decreased by a degree of significance, which verified the effectiveness of the device’s gravity balancing characteristics for MRC-2 patients.

Design and Simulation Analysis of a Robot-Assisted Gait Trainer with the PBWS System

In response to the ever-increasing demand of lower limb rehabilitation, this paper presents a novel robot-assisted gait trainer (RGT) to assist the elderly and the pediatric patients with neurological impairments in the lower limb rehabilitation training (LLRT). The RGT provides three active degrees of freedom (DoF) to both legs that are used to implement the gait cycle in such a way that the natural gait is not significantly affected. The robot consists of (i) the partial body weight support (PBWS) system to assist patients in sit-to-stand transfer via the precision linear rail system and (ii) the bipedal end-effector (BE) to control the motions of lower limbs via two mechanical arms. The robot stands out for multiple modes of training and optimized functional design to improve the quality of life for those patients. To analyze the performance of the RGT, the kinematic and static models are established in this paper. After that, the reachable workspace and motion trajectory are analyzed to cover the motion requirements and implement natural gait cycle. The preliminary results demonstrate the usability of the robot.

Adaptive Admittance Control Scheme with Virtual Reality Interaction for Robot-Assisted Lower Limb Strength Training

Muscle weakness is the primary impairment causing mobility difficulty among stroke survivors. Millions of people are unable to live normally because of mobility difficulty every year. Strength training is an effective method to improve lower extremity ability but is limited by the shortage of medical staff. Thus, this paper proposes a robot-assisted active training (RAAT) by an adaptive admittance control scheme with virtual reality interaction (AACVRI). AACVRI consists of a stiffness variable admittance controller, an adaptive controller, and virtual reality (VR) interactions. In order to provide human-robot reality interactions corresponding to virtual scenes, an admittance control law with variable stiffness term was developed to define the mechanics property of the end effector. The adaptive controller improves tracking performances by compensating interaction forces and dynamics model deviations. A virtual training environment including action following, event feedback, and competition mechanism is utilized for improving boring training experience and engaging users to maintain active state in cycling training. To verify controller performances and the feasibility of RAAT, experiments were conducted with eight subjects. Admittance control provides desired variable interactions along the trajectory. The robot responds to different virtual events by changing admittance parameters according to trigger feedbacks. Adaptive control ensures tracking errors at a low level. Subjects were maintained in active state during this strength training. Their physiological signals significantly increased, and interaction forces were at a high level. RAAT is a feasible approach for lower limb strength training, and users can independently complete high-quality active strength training under RAAT.

Effect of Robot Assisted Gait Training on Motor and Walking Function in Patients with Subacute Stroke: A Random Controlled Study

BACKGROUND

Robot-assisted gait training has been confirmed to have beneficial effect on the rehabilitation of stroke patients. An exoskeleton robot, named BEAR-H1, is designed to help stroke patients with walking disabilities.

METHODS

17 subjects in experimental group and 15 subjects in control group completed the study. The experimental group received 30 minutes of BEAR-H1 assisted gait training(BAGT), and the control group received 30 minutes of conventional training, 5 times/week for 4weeks. All subjects were evaluated with 6-minute walk test (6MWT), Fugl-Meyer Assessment for lower extremity (FMA-LE), Functional Ambulatory Classification (FAC), Modified Ashworth Scale (MAS), and gait analysis at baseline and after 4 weeks intervention.

RESULTS

The improvements of 6MWT, FMA-LE, gait speed, cadence, step length and cycle duration in BAGT group were more noticeable than in the control group. However, there was no difference in the assessment of MAS between two groups.

CONCLUSIONS

Our results showed that BAGT is an effective intervention to improve the motor and walking ability during 4 weeks training for subacute stroke patients.

Functional Gait Recovery after a Combination of Conventional Therapy and Overground Robot-Assisted Gait Training Is Not Associated with Significant Changes in Muscle Activation Pattern: An EMG Preliminary Study on Subjects Subacute Post Stroke

Background: Overground Robot-Assisted Gait Training (o-RAGT) appears to be a promising stroke rehabilitation in terms of clinical outcomes. The literature on surface ElectroMyoGraphy (sEMG) assessment in o-RAGT is limited. This paper aimed to assess muscle activation patterns with sEMG in subjects subacute post stroke after training with o-RAGT and conventional therapy. Methods: An observational preliminary study was carried out with subjects subacute post stroke who received 15 sessions of o-RAGT (5 sessions/week; 60 min) in combination with conventional therapy. The subjects were assessed with both clinical and instrumental evaluations. Gait kinematics and sEMG data were acquired before (T1) and after (T2) the period of treatment (during ecological gait), and during the first session of o-RAGT (o-RAGT₁). An eight-channel wireless sEMG device acquired in sEMG signals. Significant differences in sEMG outcomes were found in the BS of TA between T1 and T2. There were no other significant correlations between the sEMG outcomes and the clinical results between T1 and T2. Conclusions: There were significant functional gains in gait after complex intensive clinical rehabilitation with o-RAGT and conventional therapy. In addition, there was a significant increase in bilateral symmetry of the Tibialis Anterior muscles. At this stage of the signals from the tibialis anterior (TA), gastrocnemius medialis (GM), rectus femoris (RF), and biceps femoris caput longus (BF) muscles of each lower extremity. sEMG data processing extracted the Bilateral Symmetry (BS), the Co-Contraction (CC), and the Root Mean Square (RMS) coefficients. Results: Eight of 22 subjects in the subacute stage post stroke agreed to participate in this sEMG study. This subsample demonstrated a significant improvement in the motricity index of the affected lower limb and functional ambulation. The heterogeneity of the subjects’ characteristics and the small number of subjects was associated with high variability research, functional gait recovery was associated with minimal change in muscle activation patterns.

Gait Recovery with an Overground Powered Exoskeleton: A Randomized Controlled Trial on Subacute Stroke Subjects

BACKGROUND

Overground Robot-Assisted Gait Training (o-RAGT) provides intensive gait rehabilitation. This study investigated the efficacy of o-RAGT in subacute stroke subjects, compared to conventional gait training.

METHODS

A multicenter randomized controlled trial was conducted on 75 subacute stroke subjects (38 in the Experimental Group (EG) and 37 in the Control Group (CG)). Both groups received 15 sessions of gait training (5 sessions/week for 60 min) and daily conventional rehabilitation. The subjects were assessed at the beginning (T1) and end (T2) of the training period with the primary outcome of a 6 Minutes Walking Test (6MWT), the Modified Ashworth Scale of the Affected lower Limb (MAS-AL), the Motricity Index of the Affected lower Limb (MI-AL), the Trunk Control Test (TCT), Functional Ambulation Classification (FAC), a 10 Meters Walking Test (10MWT), the modified Barthel Index (mBI), and the Walking Handicap Scale (WHS).

RESULTS

The 6MWT increased in both groups, which was confirmed by both frequentist and Bayesian analyses. Similar outcomes were registered in the MI-AL, 10MWT, mBI, and MAS-AL. The FAC and WHS showed a significant number of subjects improving in functional and community ambulation in both groups at T2.

CONCLUSIONS

The clinical effects of o-RAGT were similar to conventional gait training in subacute stroke subjects. The results obtained in this study are encouraging and suggest future clinical trials on the topic.

Electromechanical-assisted training for walking after stroke

BACKGROUND

Electromechanical- and robot-assisted gait-training devices are used in rehabilitation and might help to improve walking after stroke. This is an update of a Cochrane Review first published in 2007 and previously updated in 2017.

OBJECTIVES

Primary • To determine whether electromechanical- and robot-assisted gait training versus normal care improves walking after stroke Secondary • To determine whether electromechanical- and robot-assisted gait training versus normal care after stroke improves walking velocity, walking capacity, acceptability, and death from all causes until the end of the intervention phase SEARCH METHODS: We searched the Cochrane Stroke Group Trials Register (last searched 6 January 2020); the Cochrane Central Register of Controlled Trials (CENTRAL; 2020 Issue 1), in the Cochrane Library; MEDLINE in Ovid (1950 to 6 January 2020); Embase (1980 to 6 January 2020); the Cumulative Index to Nursing and Allied Health Literature (CINAHL; 1982 to 20 November 2019); the Allied and Complementary Medicine Database (AMED; 1985 to 6 January 2020); Web of Science (1899 to 7 January 2020); SPORTDiscus (1949 to 6 January 2020); the Physiotherapy Evidence Database (PEDro; searched 7 January 2020); and the engineering databases COMPENDEX (1972 to 16 January 2020) and Inspec (1969 to 6 January 2020). We handsearched relevant conference proceedings, searched trials and research registers, checked reference lists, and contacted trial authors in an effort to identify further published, unpublished, and ongoing trials.

SELECTION CRITERIA

We included all randomised controlled trials and randomised controlled cross-over trials in people over the age of 18 years diagnosed with stroke of any severity, at any stage, in any setting, evaluating electromechanical- and robot-assisted gait training versus normal care.

DATA COLLECTION AND ANALYSIS

Two review authors independently selected trials for inclusion, assessed methodological quality and risk of bias, and extracted data. We assessed the quality of evidence using the GRADE approach. The primary outcome was the proportion of participants walking independently at follow-up.

MAIN RESULTS

We included in this review update 62 trials involving 2440 participants. Electromechanical-assisted gait training in combination with physiotherapy increased the odds of participants becoming independent in walking (odds ratio (random effects) 2.01, 95% confidence interval (CI) 1.51 to 2.69; 38 studies, 1567 participants; P < 0.00001; I² = 0%; high-quality evidence) and increased mean walking velocity (mean difference (MD) 0.06 m/s, 95% CI 0.02 to 0.10; 42 studies, 1600 participants; P = 0.004; I² = 60%; low-quality evidence) but did not improve mean walking capacity (MD 10.9 metres walked in 6 minutes, 95% CI -5.7 to 27.4; 24 studies, 983 participants; P = 0.2; I² = 42%; moderate-quality evidence). Electromechanical-assisted gait training did not increase the risk of loss to the study during intervention nor the risk of death from all causes. Results must be interpreted with caution because (1) some trials investigated people who were independent in walking at the start of the study, (2) we found variation between trials with respect to devices used and duration and frequency of treatment, and (3) some trials included devices with functional electrical stimulation. Post hoc analysis showed that people who are non-ambulatory at the start of the intervention may benefit but ambulatory people may not benefit from this type of training. Post hoc analysis showed no differences between the types of devices used in studies regarding ability to walk but revealed differences between devices in terms of walking velocity and capacity.

AUTHORS' CONCLUSIONS

People who receive electromechanical-assisted gait training in combination with physiotherapy after stroke are more likely to achieve independent walking than people who receive gait training without these devices. We concluded that eight patients need to be treated to prevent one dependency in walking. Specifically, people in the first three months after stroke and those who are not able to walk seem to benefit most from this type of intervention. The role of the type of device is still not clear. Further research should consist of large definitive pragmatic phase 3 trials undertaken to address specific questions about the most effective frequency and duration of electromechanical-assisted gait training, as well as how long any benefit may last. Future trials should consider time post stroke in their trial design.

Effect of robot-assisted gait training on biomechanics of ankle joint in patients with post-stroke hemiparesis

The key factor promoting post-stroke gait disturbances is motor impairment of the ankle joint (AJ) which results in pathological synergies. Robotic devices used for gait training are equipped with hip and knee joint actuators. However, there is no consensus in the literature on their effect on AJ movements. The aim of this study was to investigate the effect of robot-assisted gait training on AJ movements in patients with post-stroke paresis. The study recruited 22 hemispheric stroke survivors. They motor function was assessed using clinical scales and motion capture analysis. All patients received 11 robot-assisted gait training session. After rehabilitation, the total score on the Fugl-Meyer Assessment scale increased from 146.5 to 152 points (p < 0.05); for the lower limb, the score increased from 18 to 20.5 points (p < 0.05). The muscle tone of ankle extensors decreased from 2.5 to 2.0 points on the modified Ashworth scale (p < 0.05). The duration of the stance phase increased from 28.0 to 33.5% relative to the total gait cycle (GC). The main difference in the GC structure before and after rehabilitation is the presence of 3 GC parts instead of 5, suggesting consolidation of patients’ goniograms at 1-61% of GC. Comparison of joint angles before and after rehabilitation revealed that only the interquartile ranges (IR) were different (р < 0.05). The authors conclude that robot-assisted training with knee and hip joint actuators indirectly affects the kinematic parameters of AJ by promoting a shift towards the average gait kinematics.

A 4-DOF Workspace Lower Limb Rehabilitation Robot: Mechanism Design, Human Joint Analysis and Trajectory Planning

Most of currently rehabilitation robots cannot achieve the adduction/abduction (A/A) training of the hip joint and lack the consideration of the patient handling. This paper presents a four degrees of freedom (DOF) spatial workspace lower limb rehabilitation robot, and it could provide flexion/extension (F/E) training to three lower limb joints and A/A training to the hip joint. The training method is conducting the patient’s foot to complete the rehabilitation movement, and the patient could directly take training on the wheelchair and avoid frequent patient handling between the wheelchair and the rehabilitation device. Because patients own different joint range of motions (ROM), an analysis method for obtaining human joint motions is proposed to guarantee the patient’s joint safety in this training method. The analysis method is based on a five-bar linkage kinematic model, which includes the human lower limb. The human-robot hybrid kinematic model is analyzed according to the Denavit-Hartenberg (D-H) method, and a variable human-robot workspace based on the user is proposed. Two kinds of trajectory planning methods are introduced. The trajectory planning method and the human joint analysis method are validated through the trajectory tracking experiment of the prototype.