Inclusion of People With Aphasia in Stroke Trials: A Systematic Search and Review

BACKGROUND

Although people with aphasia (PwA) represent 30% of stroke survivors, they are frequently excluded from stroke research, or their inclusion is unclear. Such practice significantly limits the generalizability of stroke research, increases the need to duplicate research in aphasia-specific populations, and raises important ethical and human rights issues.

OBJECTIVE

To detail the extent and nature of inclusion of PwA in contemporary stroke randomized controlled trials (RCTs).

METHODS

We conducted a systematic search to identify completed stroke RCTs and RCT protocols published in 2019. Web of Science was searched using terms "stroke" and "randomized controlled trial". These articles were reviewed by extracting rates of PwA inclusion/exclusion, whether "aphasia" or related terms were referred to in the article or supplemental files, eligibility criteria, consent procedures, adaptations made to support the inclusion of PwA, and attrition rates of PwA. Data were summarized, and descriptive statistics applied when appropriate.

RESULTS

271 studies comprising 215 completed RCTs and 56 protocols were included. 36.2% of included studies referred to aphasia/dysphasia. Of completed RCTs, only 6.5% explicitly included PwA, 4.7% explicitly excluded PwA, and inclusion was unclear in the remaining 88.8%. Among RCT protocols, 28.6% of studies intended inclusion, 10.7% intended excluding PwA, and in 60.7%, inclusion was unclear. In 45.8% of included studies, sub-groups of PwA were excluded, either explicitly (ie, particular types/severities of aphasia, eg, global aphasia) or implicitly, by way of ambiguous eligibility criteria which could potentially relate to a sub-group of PwA. Little rationale for exclusion was provided. 71.2% of completed RCTs did not report any adaptations that could support the inclusion of PwA, and minimal information was provided about consent procedures. Where it could be determined, attrition of PwA averaged 10% (range 0%-20%).

CONCLUSION

This paper details the extent of inclusion of PwA in stroke research and highlights opportunities for improvement.

Efficacy of Robots-Assisted Therapy in Patients With Stroke: A Meta-analysis Update

BACKGROUND

Robot-assisted therapy (RAT) could address an unmet need to relieve the strain on healthcare providers and intensify treatment in the context of an increasing stroke incidence. A comprehensive meta-analysis could provide firmer data about the topic by considering methodology limitations discovered in previous reviews and providing more rigorous evidence.

OBJECTIVE

This meta-analysis study identifies RAT's efficacy for patients with stroke.

METHODS

A systematic search of the 7 databases from January 10 to February 1, 2022, located relevant publications. We used the updated Cochrane risk-of-bias checklist for 52 trials to assess the methodologic quality of the included studies. The efficacy of RAT for patients with stroke was estimated using a pooled random-effects model in the Stata 16 software application.

RESULTS

The final analysis included 2774 patients with stroke from 52 trials. In those patients, RAT was proven to improve quality of movement (mean difference, 0.15; 95% confidence interval, 0.03-0.28) and to reduce balance disturbances (mean difference, -1.28; 95% confidence interval, -2.48 to -0.09) and pain (standardized mean difference, -0.34; 95% confidence interval, -0.58 to -0.09).

CONCLUSIONS

Robot-assisted therapy seems to improve the quality of mobility and reduce balance disturbances and pain for patients with stroke. These findings will help develop advanced rehabilitation robots and could improve health outcomes by facilitating health services for healthcare providers and patients with stroke.

The Effect of Robot-Assisted Training on Arm Function, Walking, Balance, and Activities of Daily Living After Stroke: A Systematic Review and Meta-Analysis

This meta-analysis aimed to compare the effects of robot-assisted training (RAT) with those of conventional therapy (CT), considering the potential sources of heterogeneity in the previous studies. We searched three international electronic databases (MEDLINE, Embase, and the Cochrane Library) to identify relevant studies. Risk of bias assessment was performed using the Cochrane's Risk of Bias 1.0 tool. The certainty of the evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluations method. The meta-analyses for each outcome of the respective domains were performed using 24 randomized controlled trials (RCTs) on robot-assisted arm training (RAAT) for arm function, 7 RCTs on RAAT for activities of daily living (ADL), 12 RCTs on robot-assisted gait training (RAGT) for balance, 6 RCTs on RAGT for walking, and 7 RCTs on RAGT for ADL. The random-effects model for the meta-analysis revealed that RAAT has significant superiority over CT in improving arm function, and ADL. We also showed that RAGT has significant superiority over CT in improving balance. Our study provides high-level evidence for the superiority of RAT over CT in terms of functional recovery after stroke. Therefore, physicians should consider RAT as a therapeutic option for facilitating functional recovery after stroke.

End-effector lower limb robot-assisted gait training effects in subacute stroke patients: A randomized controlled pilot trial

BACKGROUND

This pilot study investigated end-effector lower limb rehabilitation robot training effects in subacute stroke patients.

METHODS

Forty-nine stroke patients were randomly assigned to 2 treatment groups: a 30-minute end-effector lower limb rehabilitation robot training plus 1.5-hour conventional physiotherapy (robot group; n = 26), or a 2-hour conventional physiotherapy (control group; n = 23). All patients received 5 treatments weekly for 4 weeks. The functional ambulatory category was the primary outcome and the motricity index, Fugl Meyer assessment-lower extremity, rivermead mobility index, 10 meter walk test, Berg balance scale, and modified Barthel index were secondary outcomes.

RESULTS

All outcome measures significantly improved in both groups after training (P > .05). The robot group improved more in FAC than the control group (P = .005).

CONCLUSIONS

Compared with conventional physiotherapy alone, end-effector lower limb robot-assisted gait training with conventional physiotherapy improved subacute stroke patients walking ability.

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.

Rehabilitation effect of intelligent rehabilitation training system on hemiplegic limb spasms after stroke

This article aimed to explore the rehabilitation efficacy of intelligent rehabilitation training systems in hemiplegic limb spasms after stroke and provided more theoretical basis for the application of intelligent rehabilitation systems in the rehabilitation of hemiplegic limb spasms after stroke. To explore the rehabilitation efficacy of intelligent rehabilitation training system (RTS for short here) in post-stroke hemiplegic limb spasms, this study selected 99 patients with post-stroke hemiplegic limb spasms admitted to a local tertiary hospital from March 2021 to March 2023 as the research subjects. This article used blind selection to randomly divide them into three groups: control group 1, control group 2, and study group, with 33 patients in each group. Control group 1 used a conventional RTS, group 2 used the brain-computer interface RTS from reference 9, and research group used the intelligent RTS from this article. This article compared the degree of spasticity, balance ability score, motor function score, and daily living activity score of three groups of patients after 10 weeks of treatment. After 10 weeks of treatment, the number of patients in the study group with no spasms at level 0 (24) was significantly higher than the number of patients in group 1 (7) and group 2 (10), with a statistically significant difference (P < 0.05); In the comparison of Barthel index scores, after ten weeks of treatment, the total number of people in the study group with scores starting at 71-80 and 81-100 was 23. The total number of people in the score range of 71-80 and 81-100 in group 1 was 5, while in group 2, the total number of people in this score range was 8. The study group scored considerably higher than the control group and the difference was found to be statistically relevant (P < 0.05). In the Berg balance assessment scale and motor function assessment scale, after 10 weeks of treatment, the scores of the study group patients on both scales were significantly higher than those of group 1 and group 2 (P < 0.05). The intelligent RTS is beneficial for promoting the improvement of spasticity in stroke patients with hemiplegic limb spasms, as well as improving their balance ability, motor ability, and daily life activities. Its rehabilitation effect is good.

Assistive Technology Involving Postural Control and Gait Performance for Adults with Stroke: A Systematic Review and Meta-Analysis

This study aimed to comprehensively summarize assistive technology devices for postural control and gait performance in stroke patients. In the study, we searched for randomized controlled trials (RCTs) published until 31 December 2022 in four electrical databases. The most frequently applied assistive technology devices involving postural stability and gait function for stroke patients were robot-assistive technology devices. Out of 1065 initially retrieved citations that met the inclusion criteria, 30 RCTs (12 studies for subacute patients and 18 studies for chronic patients) were included in this review based on eligibility criteria. The meta-analysis included ten RCTs (five studies for subacute patients and five for chronic patients) based on the inclusion criteria of the data analysis. After analyzing, the variables, only two parameters, the Berg balance scale (BBS) and the functional ambulation category (FAC), which had relevant data from at least three studies measuring postural control and gait function, were selected for the meta-analysis. The meta-analysis revealed significant differences in the experimental group compared to the control group for BBS in both subacute and chronic stroke patients and for the FAC in chronic stroke patients. Robot-assistive training was found to be superior to regular therapy in improving postural stability for subacute and chronic stroke patients but not gait function. This review suggests that robot-assistive technology devices should be considered in rehabilitative approaches for postural stability and gait function for subacute and chronic stroke patients.

Therapeutic Effects of Robotic-Exoskeleton-Assisted Gait Rehabilitation and Predictive Factors of Significant Improvements in Stroke Patients: A Randomized Controlled Trial

Robotic-exoskeleton-assisted gait rehabilitation improves lower limb strength and functions in post-stroke patients. However, the predicting factors of significant improvement are unclear. We recruited 38 post-stroke hemiparetic patients whose stroke onsets were <6 months. They were randomly assigned to two groups: a control group receiving a regular rehabilitation program, and an experimental group receiving in addition a robotic exoskeletal rehabilitation component. After 4 weeks of training, both groups showed significant improvement in the strength and functions of their lower limbs, as well as health-related quality of life. However, the experimental group showed significantly better improvement in the following aspects: knee flexion torque at 60°/s, 6 min walk test distance, and the mental subdomain and the total score on a 12-item Short Form Survey (SF-12). Further logistic regression analyses showed that robotic training was the best predictor of a greater improvement in both the 6 min walk test and the total score on the SF-12. In conclusion, robotic-exoskeleton-assisted gait rehabilitation improved lower limb strength, motor performance, walking speed, and quality of life in these stroke patients.

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.

Intensity control of robot-assisted gait training based on biometric data: Preliminary study

OBJECTIVE

This study is aimed to compare the effect of robot-assisted gait training when the intensity is controlled using patients' biometric data to when controlled by therapist's subjective judgment.

DESIGN

This is non-blinded, prospective, randomized controlled study. Patients were randomly assigned to one of two groups. In biometric data control group, exercise intensity was controlled through the patient's heart rate or rating of perceived exertion (RPE). The intensity was raised to the next level when the patient's heart rate reserve was less than 40 percent or the RPE was less than 12 points. The exercise intensity of the therapist control group was adjusted according to the judgement of a therapist. All patients were instructed to perform robot (Morning Walk®)-assisted 20-minute gait training session five times a week during 3 weeks. The primary outcome was functional ambulation category (FAC). The secondary outcomes were modified Barthel index (MBI), Berg balance scale (BBS), timed up and go test (TUG) and 10-meter walk test (10MWT) The outcomes were evaluated at baseline and after 3-week gait training.

RESULTS

A total of 55 patients with stroke were enrolled. After robotic rehabilitation, the primary outcome, FAC improved significantly (P < .05) in both groups. Also, secondary outcomes, including MBI, BBS, TUG, 10MWT, showed significant improvement (P < .05) in all groups. In addition, when comparing the functional change from baseline to week 3 between the two groups, there was no statistically significant difference in FAC (P > .05). The difference of baseline and week 3 of secondary outcome measure, MBI, BBS, TUG, 10MWT, showed no significant difference (P > .05).

CONCLUSION

In conclusion, when the robot intensity was adjusted using the patient's heart rate or RPE, the treatment effect has no significant difference to when adjusting the intensity according to the know-how of the therapist.

Efficacy and safety of EXOWALK® on electromechanical-assisted gait training: study protocol for randomized controlled trial

Background

High-intensity repetitive task-specific practice might be the most effective strategy to promote motor recovery after stroke, and electromechanical-assisted gait training represents one of the treatment options. However, there is still difficulty in clarifying the difference between conventional gait training and electromechanically assisted gait training.

Methods

The study is a multicenter, randomized, parallel-group clinical trial for stroke patients. Three clinical research centers in Korea (Dongguk University Ilsan Hospital, Chungnam National University Hospital, and Seoul National University Bundang Hospital) will participate in the clinical trial and 144 stroke patients will be registered. Enrolled patients are assigned to two groups, an experimental group and a control group, according to a randomization table. In addition, patients are treated for half an hour (one session) five times a week for 4 weeks. Both groups carry out basic rehabilitation (central nervous system development therapy and strength exercise) and the experimental group executes robotic walking rehabilitation treatment, and the control group executes conventional gait rehabilitation treatment. The primary endpoint variable is the Functional Ambulation Category (FAC) that determines the degree of independent walking and is measured before, after, and after 4 weeks of treatment. Secondary endpoint variables are 11 variables that take into account motor function and range, measured at the same time as the primary endpoint variable.

Discussion

There are still insufficient data on the effectiveness of electromechanical-assisted gait training for stroke patients and large-scale research is lacking. Thus, the research described here is a large-scale study of stroke patients that can supplement the limitations mentioned in other previous studies. In addition, the clinical studies described here include physical epidemiological analysis parameters that can determine walking ability. The results of this study can lead to prove the generalizable effectiveness and safety of electromechanical-assisted gait training with EXOWALK®.

Trial registration

Clinical Research Information Service (CRIS), Republic of Korea KCT0003411, Registered on 30 October 2018

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06660-8.

Effect of gait rehabilitation with a footpad-type locomotion interface on gait ability in subacute stroke patients

BACKGROUND: Gait rehabilitation using a footpad-type locomotion interface has been reported as effective in improving gait ability in chronic stroke patients. However, the effect on subacute stroke patients is unknown. OBJECTIVE: To compare the effect of gait rehabilitation using a footpad-type locomotion interface (Gait Training with Locomotion Interface group; GTLI group) with conventional gait rehabilitation (control group) in subacute stroke patients. METHODS: Twenty-one stroke patients (GTLI group: n = 13, control group: n = 8) participated in the study. All participants received gait rehabilitation using the footpad-type locomotion interface or conventional gait rehabilitation for 20 minutes x 20 sessions. Outcome measures were functional ambulation Category (FAC), gait speed, gait endurance and lower muscle strength. Measures were taken at baseline and 1, 2, 3 and 4 weeks. RESULT: The GTLI group significantly improved gait speed and gait endurance compared with the control group. However, FAC and lower limb muscle strength were not significantly different. CONCLUSIONS: The results suggest that gait rehabilitation using the footpad-type locomotion interface can improve gait ability better than conventional gait rehabilitation.

A Robot-Assisted Therapy to Increase Muscle Strength in Hemiplegic Gait Rehabilitation

This study examines the feasibility of using a robot-assisted therapy methodology based on the Bobath concept to perform exercises applied in conventional therapy for gait rehabilitation in stroke patients. The aim of the therapy is to improve postural control and movement through exercises based on repetitive active-assisted joint mobilization, which is expected to produce strength changes in the lower limbs. As therapy progresses, robotic assistance is gradually reduced and the patient's burden increases with the goal of achieving a certain degree of independence. The relationship between force and range of motion led to the analysis of both parameters of interest. The study included 23 volunteers who performed 24 sessions, 2 sessions per week for 12 weeks, each lasting about 1 h. The results showed a significant increase in hip abduction and knee flexion strength on both sides, although there was a general trend of increased strength in all joints. However, the range of motion at the hip and ankle joints was reduced. The usefulness of this platform for transferring exercises from conventional to robot-assisted therapies was demonstrated, as well as the benefits that can be obtained in muscle strength training. However, it is suggested to complement the applied therapy with exercises for the maintenance and improvement of the range of motion.

Efficacy of electromechanical-assisted gait training on clinical walking function and gait symmetry after brain injury of stroke: a randomized controlled trial

Electromechanical-assisted gait training may be an effective intervention to promote motor recovery after brain injury. However, many studies still have difficulties in clarifying the difference between electromechanical-assisted gait training and conventional gait training. To evaluate the effectiveness of electromechanical-assisted gait training compared to that of conventional gait training on clinical walking function and gait symmetry of stroke patients. We randomly assigned patients with stroke (n = 144) to a control group (physical therapist-assisted gait training) and an experimental group (electromechanical gait training). Both types of gait training were done for 30 min each day, 5 days a week for 4 weeks. The primary endpoint was the change in functional ambulatory category (FAC). Secondary endpoints were clinical walking functions and gait symmetries of swing time and step length. All outcomes were measured at baseline (pre-intervention) and at 4 weeks after the baseline (post-intervention). FAC showed significant improvement after the intervention, as did clinical walking functions, in both groups. The step-length asymmetry improved in the control group, but that in the experimental group and the swing-time asymmetry in both groups did not show significant improvement. In the subgroup analysis of stroke duration of 90 days, FAC and clinical walking functions showed more significant improvement in the subacute group than in the chronic group. However, gait symmetries did not show any significant changes in either the subacute or the chronic group. Electromechanically assisted gait training by EXOWALK was as effective as conventional gait training with a physiotherapist. Although clinical walking function in the subacute group improved more than in the chronic group, gait asymmetry did not improve for either group after gait training.

Trial registration: KCT0003411 Clinical Research Information Service (CRIS), Republic of Korea.

Minimal Contact Robotic Stroke Rehabilitation on Risk of COVID-19, Work Efficiency and Sensorimotor Function

Patients with hemiparetic stroke undergo direct, labor-intensive hands-on conventional physical therapy to improve sensorimotor function, spasticity, balance, trunk stability, and activities of daily living (ADLs). Currently, direct, intensive hands-on therapeutic modalities have increased concerns during the coronavirus (COVID-19) global pandemic. We developed an innovative Walkbot to mitigate the issues surrounding conventional hands-on physical therapy. We aimed to compare the effects of minimal-contact robotic rehabilitation (MRR) and full-contact conventional rehabilitation (FCR) on static and dynamic balance, trunk stability, ADLs, spasticity, and cognition changes in patients with hemiparetic stroke. A total of 64 patients with hemiparetic stroke (mean age = 66.38 ± 13.17; 27 women) underwent either MRR or FCR three times/week for 6 weeks. Clinical outcome measurements included the Trunk Impairment Scale (TIS), the Berg Balance Scale (BBS), the modified Ashworth Scale (MAS), the Fugl—Meyer Assessment (FMA), and the modified Barthel Index (MBI) scores. A 2 × 2 repeated analysis of variance (ANOVA) was performed, and an independent t-test was used to determine statistical differences in the physiotherapists’ work efficiency and COVID-19 transmission risk. The ANOVA showed that MRR had effects superior to those of FCR on the TIS, the BBS, the FMA, and the MBI (p < 0.05), but not on the MAS (p = 0.230). MRR showed a greater decrease on the physiotherapist’s work efficiency and COVID-19 transmission risk (p < 0.05). Our results provide clinical evidence that robot-assisted locomotor training helps maximize the recovery of sensorimotor function, abnormal synergy, balance, ADLs, and trunk stability, and facilitates a safer environment and less labor demand than conventional stroke rehabilitation.

Effects of Training with a Brain-Computer Interface-Controlled Robot on Rehabilitation Outcome in Patients with Subacute Stroke: A Randomized Controlled Trial

INTRODUCTION

Stroke is always associated with a difficult functional recovery process. A brain-computer interface (BCI) is a technology which provides a direct connection between the human brain and external devices. The primary aim of this study was to determine whether training with a BCI-controlled robot can improve functions in patients with subacute stroke.

METHODS

Subacute stroke patients aged 32-68 years with a course of 2 weeks to 3 months were randomly assigned to the BCI group or to the sham group for a 4-week course. The primary outcome measures were Loewenstein Occupational Therapy Cognitive Assessment (LOCTA) and Fugl-Meyer Assessment for Lower Extremity (FMA-LE). Secondary outcome measures included Fugl-Meyer Assessment for Balance (FMA-B), Functional Ambulation Category (FAC), Modified Barthel Index (MBI), serum brain-derived neurotrophic factor (BDNF) levels and motor-evoked potential (MEP).

RESULTS

A total of 28 patients completed the study. Both groups showed a significant increase in mean LOCTA (sham: P < 0.001, Cohen's d =  - 2.972; BCI: P < 0.001, Cohen's d =  - 4.266) and FMA-LE (sham: P < 0.001, Cohen's d =  - 3.178; BCI: P < 0.001, Cohen's d =  - 3.063) scores. The LOCTA scores in the BCI group were 14.89% higher than in the sham group (P = 0.049, Cohen's d =  - 0.580). There were no significant differences between the two groups in terms of FMA-B (P = 0.363, Cohen's d =  - 0.252), FAC (P = 0.363), or MBI (P = 0.493, Cohen's d =  - 0.188) scores. The serum levels of BDNF were significantly higher within the BCI group (P < 0.001, Cohen's d =  - 1.167), and the MEP latency decreased by 3.75% and 4.71% in the sham and BCI groups, respectively.

CONCLUSION

Training with a BCI-controlled robot combined with traditional physiotherapy promotes cognitive function recovery, and enhances motor functions of the lower extremity in patients with subacute stroke. These patients also showed increased secretion of BDNF.

TRIAL REGISTRATION

Chinese clinical trial registry: ChiCTR-INR-17012874.

Effects of robot (SUBAR)-assisted gait training in patients with chronic stroke: Randomized controlled trial

BACKGROUND

SUBAR is a new ground walking exoskeletal robot. The objective of this study is to investigate SUBAR-assisted gait training's effects in patients with chronic stroke.

METHODS

This preliminary study is a prospective randomized controlled trial. Thirty adults were enrolled 6 months after the onset of stroke with functional ambulation category scores ≥ 3. Patients were randomly assigned to receive robot-assisted gait training (SUBAR group, n = 15) or conventional physiotherapy (control group, n = 15). All patients received a total of 10 treatment sessions of 30 minutes each for 3 weeks. Before and after the 10-treatment sessions, patients were evaluated. The primary outcome is the 10 meter walk test and the secondary outcomes were the functional ambulation category scale, the Motricity Index-Lower, Modified Ashworth Scale (MAS), timed up and go, Rivermead Mobility Index, Berg Balance Scale (BBS), and gait analysis.

RESULTS

In the SUBAR group, MAS and step length were significantly improved between pre- and posttreatment measurements (Δmean ± SD: -1.1 ± 1.6 and 5.5 ± 7.6, P = .019 and .016, respectively). The SUBAR group improved the stride length and step length of the affected limb but not significantly. The control group had significant improvements in the BBS, MAS, and stride length between pre- and posttreatment measurements (Δmean ± SD: 3.5 ± 4.6, -0.8 ± 1.5, and 6.5 ± 9.5; P = .004, .031, and .035, respectively). The BBS improved more in the control group than in the SUBAR group. There were no other differences between the SUBAR group and the control group.

CONCLUSION

Our results suggest that SUBAR-assisted gait training improved gait parameters in patients with chronic stroke. However, there was no significant difference in most outcome measures compared to conventional physiotherapy. Further research is warranted to measure the effects of SUBAR-assisted gait training.

Robot-Assisted Gait Training Plan for Patients in Poststroke Recovery Period: A Single Blind Randomized Controlled Trial

Background

Walking dysfunction exists in most patients after stroke. Evidence regarding gait training in two weeks is scarce in resource-limited settings; this study was conducted to investigate the effects of a short-term robot-assisted gait training plan for patients with stroke.

Methods

85 patients were randomly assigned to one of two treatment groups, with 31 patients in withdrawal before treatment. The training program comprised 14 2-hour sessions, for 2 consecutive weeks. Patients allocated to the robot-assisted gait training group were treated using the Gait Training and Evaluation System A3 from NX (RT group, n = 27). Another group of patients was allocated to the conventional overground gait training group (PT group, n = 27). Outcome measurements were assessed using time-space parameter gait analysis, Fugl-Meyer Assessment (FMA), and Timed Up and Go test (TUG) scores.

Results

In the time-space parameter analysis of gait, the two groups exhibited no significant changes in time parameters, but the RT group exhibited a significant effect on changes in space parameters (stride length, walk velocity, and toe out angle, P < 0.05). After training, FMA scores (20.22 ± 2.68) of the PT group and FMA scores (25.89 ± 4.6) of the RT group were significant. In the Timed Up and Go test, FMA scores of the PT group (22.43 ± 3.95) were significant, whereas those in the RT group (21.31 ± 4.92) were not. The comparison between groups revealed no significant differences.

Conclusion

Both the RT group and the PT group can partially improve the walking ability of stroke patients within 2 weeks.

The effect of robot-assisted gait training on cortical activation in stroke patients: A functional near-infrared spectroscopy study

OBJECTIVE

To investigate the effects of the robot-assisted gait training on cortical activation and functional outcomes in stroke patients.

METHODS

The patients were randomly assigned: training with Morning Walk® (Morning Walk group; n = 30); conventional physiotherapy (control group; n = 30). Rehabilitation was performed five times a week for 3 weeks. The primary outcome was the cortical activation in the Morning Walk group. The secondary outcomes included gait speed, 10-Meter Walk Test (10MWT), FAC, Motricity Index-Lower (MI-Lower), Modified Barthel Index (MBI), Rivermead Mobility Index (RMI), and Berg Balance Scale (BBS).

RESULTS

Thirty-six subjects were analyzed, 18 in the Morning Walk group and 18 in the control group. The cortical activation was lower in affected hemisphere than unaffected hemisphere at the beginning of robot rehabilitation. After training, the affected hemisphere achieved a higher increase in cortical activation than the unaffected hemisphere. Consequently, the cortical activation in affected hemisphere was significantly higher than that in unaffected hemisphere (P = 0.036). FAC, MBI, BBS, and RMI scores significantly improved in both groups. The Morning Walk group had significantly greater improvements than the control group in 10MWT (P = 0.017), gait speed (P = 0.043), BBS (P = 0.010), and MI-Lower (P = 0.047) scores.

CONCLUSION

Robot-assisted gait training not only improved functional outcomes but also increased cortical activation in stroke patients.

What the Tech? The Management of Neurological Dysfunction Through the Use of Digital Technology

Worldwide, it is estimated that millions of individuals suffer from a neurological disorder which can be the result of head injuries, ischaemic events such as a stroke, or neurodegenerative disorders such as Parkinson's disease (PD) and multiple sclerosis (MS). Problems with mobility and hemiparesis are common for these patients, making daily life, social factors and independence heavily affected. Current therapies aimed at improving such conditions are often tedious in nature, with patients often losing vital motivation and positive outlook towards their rehabilitation. The interest in the use of digital technology in neuro-rehabilitation has skyrocketed in the past decade. To gain insight, a systematic review of the literature in the field was conducting following the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines for three categories: stroke, Parkinson's disease and multiple sclerosis. It was found that the majority of the literature (84%) was in favour of the use of digital technologies in the management of neurological dysfunction; with some papers taking a "neutral" or "against" standpoint. It was found that the use of technologies such as virtual reality (VR), robotics, wearable sensors and telehealth was highly accepted by patients, helped to improve function, reduced anxiety and make therapy more accessible to patients living in more remote areas. The most successful therapies were those that used a combination of conventional therapies and new digital technologies.

Five-day rehabilitation of patients undergoing total knee arthroplasty using an end-effector gait robot as a neuromodulation blending tool for deafferentation, weight offloading and stereotyped movement: Interim analysis

Deafferentation and weight offloading can increase brain and spinal motor neuron excitability, respectively. End-effector gait robots (EEGRs) can blend these effects with stereotyped movement-induced neuroplasticity. The authors aimed to evaluate the usefulness of EEGRs as a postoperative neuro-muscular rehabilitation tool. This prospective randomized controlled trial included patients who had undergone unilateral total knee arthroplasty (TKA). Patients were randomly allocated into two groups: one using a 200-step rehabilitation program in an EEGR or the other using a walker on a floor (WF) three times a day for five weekdays. The two groups were compared by electrophysiological and biomechanical methods. Since there were no more enrollments due to funding issues, interim analysis was performed. Twelve patients were assigned to the EEGR group and eight patients were assigned to the WF group. Although the muscle volume of the quadriceps and hamstring did not differ between the two groups, the normalized peak torque of the operated knee flexors (11.28 ± 16.04 Nm/kg) was improved in the EEGR group compared to that of the operated knee flexors in the WF group (4.25 ± 14.26 Nm/kg) (p = 0.04). The normalized compound motor action potentials of the vastus medialis (VM) and biceps femoris (BF) were improved in the EEGR group (p < 0.05). However, the normalized real-time peak amplitude and total, mean area under the curve of VM were decreased during rehabilitation in the EEGR group (p < 0.05). No significant differences were found between operated and non-operated knees in the EEGR group. Five-day EEGR-assisted rehabilitation induced strengthening in the knee flexors and the muscular reactivation of the BF and VM after TKA, while reducing the real-time use of the VM. This observation may suggest the feasibility of this technique: EEGR modulated the neuronal system of the patients rather than training their muscles. However, because the study was underpowered, all of the findings should be interpreted with the utmost caution.

AI Therapist Realizing Expert Verbal Cues for Effective Robot-Assisted Gait Training

Repetitive and specific verbal cues by a therapist are essential in aiding a patient's motivation and improving the motor learning process. The verbal cues comprise various expressions, sentences, volumes, and timings, depending on the therapist's proficiency. This paper proposes an AI therapist (AI-T) that implements the verbal cues of professional therapists having extensive experience with robot-assisted gait training using the SUBAR for stroke patients. The AI-T was developed using a neuro-fuzzy system, a machine learning technique leveraging the benefits of fuzzy logic and artificial neural networks. The AI-T was trained with the professional therapist's verbal cue data, as well as clinical and robotic data collected from robot-assisted gait training with real stroke patients. Ten clinical data and 16 robotic data are input variables, and six verbal cues are output variables. Fifty-eight stroke patients wore the SUBAR, a gait training robot, and participated in the robot-assisted gait training. A total of 9059 verbal cue data, 580 clinical data of stroke patients, and 144 944 robotic data were collected from 693 training sessions. Test results show that the trained AI-T can implement six types of verbal cues with 93.7% accuracy for the 1812 verbal cue data of the professional therapist. Currently, the trained AI-T is deployed in the SUBAR and provides six verbal cues to stroke patients in robot-assisted gait training.

Occurrence and Type of Adverse Events During the Use of Stationary Gait Robots-A Systematic Literature Review

Robot-assisted gait training (RAGT) devices are used in rehabilitation to improve patients' walking function. While there are some reports on the adverse events (AEs) and associated risks in overground exoskeletons, the risks of stationary gait trainers cannot be accurately assessed. We therefore aimed to collect information on AEs occurring during the use of stationary gait robots and identify associated risks, as well as gaps and needs, for safe use of these devices. We searched both bibliographic and full-text literature databases for peer-reviewed articles describing the outcomes of stationary RAGT and specifically mentioning AEs. We then compiled information on the occurrence and types of AEs and on the quality of AE reporting. Based on this, we analyzed the risks of RAGT in stationary gait robots. We included 50 studies involving 985 subjects and found reports of AEs in 18 of those studies. Many of the AE reports were incomplete or did not include sufficient detail on different aspects, such as severity or patient characteristics, which hinders the precise counts of AE-related information. Over 169 device-related AEs experienced by between 79 and 124 patients were reported. Soft tissue-related AEs occurred most frequently and were mostly reported in end-effector-type devices. Musculoskeletal AEs had the second highest prevalence and occurred mainly in exoskeleton-type devices. We further identified physiological AEs including blood pressure changes that occurred in both exoskeleton-type and end-effector-type devices. Training in stationary gait robots can cause injuries or discomfort to the skin, underlying tissue, and musculoskeletal system, as well as unwanted blood pressure changes. The underlying risks for the most prevalent injury types include excessive pressure and shear at the interface between robot and human (cuffs/harness), as well as increased moments and forces applied to the musculoskeletal system likely caused by misalignments (between joint axes of robot and human). There is a need for more structured and complete recording and dissemination of AEs related to robotic gait training to increase knowledge on risks. With this information, appropriate mitigation strategies can and should be developed and implemented in RAGT devices to increase their safety.

Morning Walk®-Assisted Gait Training Improves Walking Ability and Balance in Patients with Ataxia: a Randomized Controlled Trial

This study aimed to investigate walking ability and balance improvement of patients with ataxia caused by brain lesions after end-effector type robot (Morning Walk^®)-assisted gait training. This study randomly assigned 19 patients to one of two groups: 30 minutes of Morning Walk^® training with 1 hour of conventional physiotherapy (Morning Walk^® group; n = 10) or 1.5 hours of conventional physiotherapy (Control group; n = 9). Five treatment sessions per week were given for 3 weeks. The primary outcomes were walking ability and balance, which were assessed by the functional ambulation category (FAC) and Berg Balance Scale (BBS), respectively. The secondary outcomes included 10-meter Walk Test (10mWT), Rivermead Mobility Index (RMI), Motricity Index (MI), and Modified Barthel Index (MBI). At baseline, there was no statistically significant difference between the two groups except MBI. After the treatment, the Morning Walk^® group showed significant improvement in the FAC, BBS, 10mWT, RMI and MBI. The control group showed significant improvement in the BBS, 10mWT, RMI and MBI. Inter-group comparison demonstrated that the ∆FAC, ∆10mWT and ∆RMI of the Morning Walk^® group were significantly higher than those of the control group. Our results suggest that the patients with ataxia receiving Morning Walk^®-assisted gait training might improve greater in walking ability and balance than those trained with conventional physiotherapy.

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.