Does Robot-Assisted Gait Rehabilitation Improve Balance in Stroke Patients? A Systematic Review Eva Swinnen, MSc, PT,1,2,3 David Beckwée, MSc, PT,2 Romain Meeusen, PhD, PT,1,3 Jean-Pierre Baeyens, PhD, PT, MT,1,4 and Eric Kerckhofs, PhD, PT1,2,3 1 Faculty of Physical Education and Physiotherapy, Advanced Rehabilitation Technology and Science (ARTS), Vrije Universiteit Brussel, Brussels, Belgium; 2Faculty of Physical Education and Physiotherapy, Rehabilitation Research, Vrije Universiteit Brussel, Brussels, Belgium; 3 Center for Neuroscience, Vrije Universiteit Brussel, Brussels, Belgium; 4Physiotherapy, University College Thim van der Laan, Landquart, Switzerland
The aim of this systematic review was to summarize the improvements in balance after robot-assisted gait training (RAGT) in stroke patients. Two databases were searched: PubMed and Web of Knowledge. The most important key words are “stroke,” “RAGT,” “balance,” “Lokomat,” and “gait trainer.” Studies were included if stroke patients were involved in RAGT protocols, and balance was determined as an outcome measurement. The articles were checked for methodological quality by 2 reviewers (Cohen’s κ = 0.72). Nine studies were included (7 true experimental and 2 pre-experimental studies; methodological quality score, 56%-81%). In total, 229 subacute or chronic stroke patients (70.5% male) were involved in RAGT (3 to 5 times per week, 3 to 10 weeks, 12 to 25 sessions). In 5 studies, the gait trainer was used; in 2, the Lokomat was used; in 1 study, a single-joint wearable knee orthosis was used; and in 1 study, the AutoAmbulator was used. Eight studies compared RAGT with other gait rehabilitation methods. Significant improvements (no to large effect sizes, Cohen’s d = 0.01 to 3.01) in balance scores measured with the Berg Balance Scale, the Tinetti test, postural sway tests, and the Timed Up and Go test were found after RAGT. No significant differences in balance between the intervention and control groups were reported. RAGT can lead to improvements in balance in stroke patients; however, it is not clear whether the improvements are greater compared with those associated with other gait rehabilitation methods. Because a limited number of studies are available, more specific research (eg, randomized controlled trials with larger, specific populations) is necessary to draw stronger conclusions. Key words: Berg Balance Scale, balance, gait, robot assistance, stroke
S
troke is a frequent health care problem and one of the most common causes of death and acquired adult disability. Many patients survive stroke, but there are often long-term consequences for the patients and their families.1,2 Frequently impaired are mobility and stability of joints, muscle power, tone and reflexes, muscle endurance, control of movement, and gait pattern functions. These impairments lead to problems with transferring, maintaining body position, mobility, balance, and walking.1,3-5 In the first 6 months post stroke, almost all patients experience at least some predictable degree of functional recovery.6 Although the majority of stroke patients learn to walk independently by 6 months post Corresponding author: Eva Swinnen, Faculty of Physical Education and Physiotherapy, Advanced Rehabilitation Technology and Science (ARTS), Rehabilitation Research (RERE), Vrije Universiteit Brussel, Laarbeeklaan 103, B-1090 Brussels, Belgium; phone/fax: +32-24774529; e-mail: [email protected]
stroke, gait and balance problems persist through the chronic stages of the condition and have a significant impact on patients’ quality of life.7,8 Promising interventions that could improve aspects of gait include high-intensity therapy and repetitive-task training.1 Gait training, with the use of robot devices, helps the patients retrain motor coordination by means of task-specific repetitive practice.8 There is some evidence that stroke patients who receive robot-assisted gait training (RAGT) in combination with physiotherapy are more likely to achieve independent walking than patients who receive gait training alone.9 This is in contrast to findings in other neurological populations (such as persons with spinal cord injury and multiple Top Stroke Rehabil 2014;21(2):87–100 © 2014 Thomas Land Publishers, Inc. www.strokejournal.com doi: 10.1310/tsr2102-87
87
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sclerosis) for whom no clear evidence is found that RAGT improves walking function more than other locomotor training strategies.10-12 Balance is described as a complex motor skill that depends on interactions between multiple sensorimotor processes and environmental and functional contexts.13 After stroke, these functions could be affected individually or in combination, differing in severity of balance impairment.13 Stroke patients show an uneven weight distribution during standing but also during functional movements. These balance impairments may contribute to disordered gait. Many stroke patients are unable to benefit from gait rehabilitation because their balance control is impaired. Balance training with a focus on symmetry of stance and weight bearing contributes to the goals of rehabilitation in stroke patients.14-16 Balance training improves balance performance; pre-gait balance training also shows beneficial effects on gait function.14,17 Gait training by itself could improve balance in stroke patients. The effects of treadmill training may transfer beyond gait to positively influence balance.18-20 This review focuses on the effect of RAGT on balance. We expect that less active balance control is necessary during RAGT compared with conventional gait training because of the fixation and guidance of the robot, the body weight support (BWS) harness, or both. As a consequence, fewer improvements in balance may occur after RAGT. The research questions posed in this systematic review are as follows: (1) Are there improvements in balance-related outcome measurements after RAGT in stroke patients (within-group differences)? (2) If there are improvements measured after RAGT, are these improvements in balance greater than those measured after other gait rehabilitation methods (between-group differences)?
Methods Search strategy
A computerized search was conducted for English-language articles published before May 2013. The electronic databases PubMed and Web of Knowledge were reviewed. Key words, MeSH terms, and their combinations were organized according to the population, intervention,
comparison, and outcome (PICO) model (Table 1).21 In addition, the reference lists of the articles and narrative reviews were scanned for relevant publications. Inclusion and exclusion criteria
Included were studies on adult (>18 years) persons after stroke, regardless of duration after stroke, and effect studies on RAGT that encompassed balancerelated outcome measurements. Studies were included if at least one of the intervention groups received RAGT exclusively as an intervention. For example, if RAGT was combined with functional electrostimulation (FES), the study was excluded. Studies with outcomes focused exclusively on physical capacity, electromyographic or kinematic data, and/or cardiorespiratory functioning were excluded. Animal studies were also excluded. Pre-experimental, quasi-experimental, and true experimental studies were included, with the exception of studies that were only presented in abstract form for a congress. In this systematic review, outcome measurements related to static or dynamic balance were included. Balance was defined as postural balance, that is, the visual, vestibular, somatosensory, and proprioceptive feedback mechanisms responsible for maintaining the body in balance.13
Methodological quality assessment
After making selections based on title, abstract, and full text, the included studies were sorted into 3 categories: true experimental studies (randomized controlled trials [RCTs]), quasi-experimental trials (clinical trials without random assignment), and pre-experimental trials (ie, case reports, uncontrolled trials).22 The methodology checklist, Evaluation of Quality of an Intervention Study, was used to assess the quality of the included studies.23 This checklist scores the internal validity of the studies and consists of 7 subscales: Study Question, Study Design, Subjects, Intervention, Outcomes, Analysis, and Recommendations.23 As described in previous reports, a quality assessment procedure was used.10,11 We decided to exclude studies with a score below 50%. Two researchers scored the studies independently, and Cohen’s kappa was used
Does Robot Training Improve Balance After Stroke?
Table 1.
89
Key words and MeSH terms used in search following the PICO method
Population
Intervention
Stroke, hemiplegia, hemiparetic, CVA
RAGT, robot-assisted gait rehabilitation, robotassisted step training, step training, robotassisted step rehabilitation, step rehabilitation, motorized training, motorized rehabilitation, automatic orthosis, locomotor rehabilitation, locomotor training, Lokomat,a gait trainer,b robotics, gait orthosis
Comparison
Outcome BBS, Clinical Test of Sensory Interaction and Balance, Functional Reach Test, Tinetti test, trunk control test, TUG test, balance, stability
Note: The terms in the columns are allied with “OR.” “AND” was used between the Population, Intervention, Comparison, and Outcome columns. BBS = Berg Balance Scale; CVA = cerebrovascular accident; TUG = Timed Up and Go. a Manufactured by Hocoma (Zurich, Switzerland).
to test inter-rater reliability.24 In case of disagreement between the 2 evaluators, a consensus was pursued through discussion. If no agreement was found, a third evaluator made the decision.24 Effect size calculations
Cohen’s d was used for effect size calculation, using the differences between 2 means divided by the pooled standard deviations. An effect size from 0.2 to 0.5 was defined as small, from 0.5 to 0.8 as medium, and from 0.8 to infinity as large.25 Results Figure 1 provides an overview of the search strategy. Methodological quality scores
Ten studies were scored for methodological quality. Cohen’s kappa between the scores of the 2 researchers was 0.72, indicating a good agreement. After discussion, a consensus was found for all disagreements. Table 2 presents an overview of the scores of the methodology checklist. One study was excluded because of a methodological score below the cut-off point described in the Methods section.26 In total, 9 studies27-35 were included in this systematic literature study. Seven were true experimental studies,28,30-35 and 2 were pre-experimental studies.27,29 Descriptive analysis
Following the PICO method, Table 3 presents the main characteristics of the included studies.
If possible, effect size calculations (Cohen’s d) were performed and are reported in Table 4. In 2 studies, only the mean values were reported without their standard deviations; as a consequence, no effect size could be calculated for these data.30,34 Study design
In total, 359 stroke patients were included in the various studies: 229 of the participants (70.5% male) received RAGT, and the other 130 were included in the control groups. One hundred sixty-four had left hemiparesis, 148 had right hemiparesis, and 7 had tetraplegia. In one study (n = 40), the side of the hemiparesis was not reported.34 The mean time after stroke varied greatly among the studies (from 2.3 weeks to 48.5 months). The mean age of the participants ranged from 48.11 to 70.35 years. In all true experimental studies, the intervention and control groups were comparable at baseline, with the exception of one study in which a significant difference in age (P < .05) was found between the 2 groups.30 Using a linear regression model, the authors found that age was not related to improvements in gait; therefore, no corrections were made for age.30 Hidler et al30 reported that at 3-month follow-up,7 participants were lost to follow-up (5 in the intervention group and 2 in the control group). Ng, Tong, and Li35 and Tong, Ng, and Li32 reported that after 4 weeks of training, 4 participants in the control group were lost to follow up. Peurala et al28 stated that at 3-month follow-up, 2 participants (1 in the RAGT without FES group and 1 in the control group) were lost to follow-up. All loss to follow-up was for reasons not related to the therapy itself. In the experimental
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TOPICS IN STROKE REHABILITATION/MAR-APR 2014
After key word search: PubMed: 208 hits Web of knowledge: 347
After reading title and removing duplicates: 60
Exclusion after reading abstract: 47 (children: 1; no effect study: 2; no outcome on balance: 2; RAGT only in comb with FES: 1; upper extremity: 8; no robot: 25; language: 2; reviews and technical papers: 6)
After reading abstract: 13
Exclusion after reading fulltext: 3 (no robot: 1; upper extremity: 1; no outcome on balance: 1)
Finally included: 10
Figure 1. Flowchart search strategy. comb = combination; FES = functional electrostimulation; RAGT = robot-assisted gait training. Table 2.
Methodological quality scores
Evaluation criteria Study question (/2) Study design (/14) Subjects (/8) Intervention (/6) Outcomes (/6) Analysis (/10) Recommendations (/2) Total quality score (/48) a
True experimental. Pre-experimental.
b
Dias et al34a
Hidler et al30a
Peurala et al28a
Ng Tong et al35a et al32a
2 12 5 5 5 8 2
2 10 7 5 6 6 2
2 11 6 4 5 8 2
2 10 6 5 5 8 2
39 (81%)
38 (79%)
38 (79%)
38 (79%)
2 11 6 5 3 8 2 37 (77%)
Westlake et al33a
Fisher et al31a
Conesa et al27b
Wong et al29b
Krishnan et al26b
Mean score
2 10 5 5 5 8 2
2 10 6 4 3 6 2
2 7 4 2 4 7 2
2 8 4 2 5 4 2
2 6 2 2 3 4 2
2 9.5 5 4 4.5 6.5 2
28 (58%)
27 (56%)
21 (44%)
33.5 (70%)
37 (77%)
33 (69%)
n=33; 21 M/12 F Age: 59.9 ± 11.3 y Time post stroke: 110.9 ± 62.5 d Side of hemiplegia: 22 L/11 R
Gait trainer: n=15; 13 M/ 2F Age: 51.2 ± 7.9 y Time post stroke: 2.4 ± 2.6 y Side of hemiplegia: 8 L/7 R Gait trainer + FES: n=15; 13 M/2 F Age: 53.3 ± 8.9 y Time post stroke: 2.6 ± 2.4 y Side of hemiplegia: 9 L/6 R Gait trainer: n=17; 11 M/6 F Age: 66.6 ± 11.3 y Time post stroke: 2.7 ± 1.2 wk Side of hemiplegia: 9 L/8 R Gait trainer + FES: n=15; 10 M/5 F Age: 62 ± 10 y Time post stroke: 2.3 ± 1.1 wk Side of hemiplegia: 9 L/6 R
Hidler et al30 True exp (MQS: 79%)
Peurala et al28 True exp (MQS: 79%)
Ng et al35 True exp (MQS: 79%)
n=20; 16 M/4 F Age: 70.35 ± 7.35 y Time post stroke: 47.10 ± 63.83 mo
Participants in intervention groups
n=21; 13 M/8 F Age: 73.4 ± 11.5 y Time post stroke: 2.5 ± 1.2 wk Side of hemiplegia: 13 L/8 R
n=15; 11 M/4 F Age: 52.3 ± 6.8 y Time post stroke: 4.0 ± 5.8 y Side of hemiplegia: 5 L/10 R
n=30; 18 M/12 F Age: 54.6 ± 9.4 y Time post stroke: 138.9 ± 60.9 d Side of hemiplegia: 13 L/17 R
n=20; 14 M/6 F Age: 68 ± 10.69 y Time post stroke: 48.45 ± 29.51 mo
Participants in control groups
Population
Descriptive analysis of the included studies
Dias et al34 True exp (MQS: 81%)
Table 3.
5×/wk, 3 wk, 15 sessions of 20 min + other PT (55 min 5 ×/wk)
3×/wk, 8 to 10 wk, 24 sessions, 90 min (45 min of effective therapy)
5×/wk, for 5 wk, 40 min (including 20 min of mobilization + muscle training), 25 sessions
Training frequency
Lokomat 1.5 k/h, 40% BWS When sessions were increased, there were improvements in gait speed, decrease in BWS Gait trainer Gait trainer + FES 0 to 2 k/h When sessions were increased, there were improvements in gait speed, decrease in BWS (aiming to support
The aim of this systematic review was to summarize the improvements in balance after robot-assisted gait training (RAGT) in stroke patients. Two databases were searched: PubMed and Web of Knowledge. The most important key words are “stroke,” “RAGT,” “balance,” “Lokomat,” and “gait trainer.” Studies were included if stroke patients were involved in RAGT protocols, and balance was determined as an outcome measurement. The articles were checked for methodological quality by 2 reviewers (Cohen’s κ = 0.72). Nine studies were included (7 true experimental and 2 pre-experimental studies; methodological quality score, 56%-81%). In total, 229 subacute or chronic stroke patients (70.5% male) were involved in RAGT (3 to 5 times per week, 3 to 10 weeks, 12 to 25 sessions). In 5 studies, the gait trainer was used; in 2, the Lokomat was used; in 1 study, a single-joint wearable knee orthosis was used; and in 1 study, the AutoAmbulator was used. Eight studies compared RAGT with other gait rehabilitation methods. Significant improvements (no to large effect sizes, Cohen’s d = 0.01 to 3.01) in balance scores measured with the Berg Balance Scale, the Tinetti test, postural sway tests, and the Timed Up and Go test were found after RAGT. No significant differences in balance between the intervention and control groups were reported. RAGT can lead to improvements in balance in stroke patients; however, it is not clear whether the improvements are greater compared with those associated with other gait rehabilitation methods. Because a limited number of studies are available, more specific research (eg, randomized controlled trials with larger, specific populations) is necessary to draw stronger conclusions. Key words: Berg Balance Scale, balance, gait, robot assistance, stroke
S
troke is a frequent health care problem and one of the most common causes of death and acquired adult disability. Many patients survive stroke, but there are often long-term consequences for the patients and their families.1,2 Frequently impaired are mobility and stability of joints, muscle power, tone and reflexes, muscle endurance, control of movement, and gait pattern functions. These impairments lead to problems with transferring, maintaining body position, mobility, balance, and walking.1,3-5 In the first 6 months post stroke, almost all patients experience at least some predictable degree of functional recovery.6 Although the majority of stroke patients learn to walk independently by 6 months post Corresponding author: Eva Swinnen, Faculty of Physical Education and Physiotherapy, Advanced Rehabilitation Technology and Science (ARTS), Rehabilitation Research (RERE), Vrije Universiteit Brussel, Laarbeeklaan 103, B-1090 Brussels, Belgium; phone/fax: +32-24774529; e-mail: [email protected]
stroke, gait and balance problems persist through the chronic stages of the condition and have a significant impact on patients’ quality of life.7,8 Promising interventions that could improve aspects of gait include high-intensity therapy and repetitive-task training.1 Gait training, with the use of robot devices, helps the patients retrain motor coordination by means of task-specific repetitive practice.8 There is some evidence that stroke patients who receive robot-assisted gait training (RAGT) in combination with physiotherapy are more likely to achieve independent walking than patients who receive gait training alone.9 This is in contrast to findings in other neurological populations (such as persons with spinal cord injury and multiple Top Stroke Rehabil 2014;21(2):87–100 © 2014 Thomas Land Publishers, Inc. www.strokejournal.com doi: 10.1310/tsr2102-87
87
88
TOPICS IN STROKE REHABILITATION/MAR-APR 2014
sclerosis) for whom no clear evidence is found that RAGT improves walking function more than other locomotor training strategies.10-12 Balance is described as a complex motor skill that depends on interactions between multiple sensorimotor processes and environmental and functional contexts.13 After stroke, these functions could be affected individually or in combination, differing in severity of balance impairment.13 Stroke patients show an uneven weight distribution during standing but also during functional movements. These balance impairments may contribute to disordered gait. Many stroke patients are unable to benefit from gait rehabilitation because their balance control is impaired. Balance training with a focus on symmetry of stance and weight bearing contributes to the goals of rehabilitation in stroke patients.14-16 Balance training improves balance performance; pre-gait balance training also shows beneficial effects on gait function.14,17 Gait training by itself could improve balance in stroke patients. The effects of treadmill training may transfer beyond gait to positively influence balance.18-20 This review focuses on the effect of RAGT on balance. We expect that less active balance control is necessary during RAGT compared with conventional gait training because of the fixation and guidance of the robot, the body weight support (BWS) harness, or both. As a consequence, fewer improvements in balance may occur after RAGT. The research questions posed in this systematic review are as follows: (1) Are there improvements in balance-related outcome measurements after RAGT in stroke patients (within-group differences)? (2) If there are improvements measured after RAGT, are these improvements in balance greater than those measured after other gait rehabilitation methods (between-group differences)?
Methods Search strategy
A computerized search was conducted for English-language articles published before May 2013. The electronic databases PubMed and Web of Knowledge were reviewed. Key words, MeSH terms, and their combinations were organized according to the population, intervention,
comparison, and outcome (PICO) model (Table 1).21 In addition, the reference lists of the articles and narrative reviews were scanned for relevant publications. Inclusion and exclusion criteria
Included were studies on adult (>18 years) persons after stroke, regardless of duration after stroke, and effect studies on RAGT that encompassed balancerelated outcome measurements. Studies were included if at least one of the intervention groups received RAGT exclusively as an intervention. For example, if RAGT was combined with functional electrostimulation (FES), the study was excluded. Studies with outcomes focused exclusively on physical capacity, electromyographic or kinematic data, and/or cardiorespiratory functioning were excluded. Animal studies were also excluded. Pre-experimental, quasi-experimental, and true experimental studies were included, with the exception of studies that were only presented in abstract form for a congress. In this systematic review, outcome measurements related to static or dynamic balance were included. Balance was defined as postural balance, that is, the visual, vestibular, somatosensory, and proprioceptive feedback mechanisms responsible for maintaining the body in balance.13
Methodological quality assessment
After making selections based on title, abstract, and full text, the included studies were sorted into 3 categories: true experimental studies (randomized controlled trials [RCTs]), quasi-experimental trials (clinical trials without random assignment), and pre-experimental trials (ie, case reports, uncontrolled trials).22 The methodology checklist, Evaluation of Quality of an Intervention Study, was used to assess the quality of the included studies.23 This checklist scores the internal validity of the studies and consists of 7 subscales: Study Question, Study Design, Subjects, Intervention, Outcomes, Analysis, and Recommendations.23 As described in previous reports, a quality assessment procedure was used.10,11 We decided to exclude studies with a score below 50%. Two researchers scored the studies independently, and Cohen’s kappa was used
Does Robot Training Improve Balance After Stroke?
Table 1.
89
Key words and MeSH terms used in search following the PICO method
Population
Intervention
Stroke, hemiplegia, hemiparetic, CVA
RAGT, robot-assisted gait rehabilitation, robotassisted step training, step training, robotassisted step rehabilitation, step rehabilitation, motorized training, motorized rehabilitation, automatic orthosis, locomotor rehabilitation, locomotor training, Lokomat,a gait trainer,b robotics, gait orthosis
Comparison
Outcome BBS, Clinical Test of Sensory Interaction and Balance, Functional Reach Test, Tinetti test, trunk control test, TUG test, balance, stability
Note: The terms in the columns are allied with “OR.” “AND” was used between the Population, Intervention, Comparison, and Outcome columns. BBS = Berg Balance Scale; CVA = cerebrovascular accident; TUG = Timed Up and Go. a Manufactured by Hocoma (Zurich, Switzerland).
to test inter-rater reliability.24 In case of disagreement between the 2 evaluators, a consensus was pursued through discussion. If no agreement was found, a third evaluator made the decision.24 Effect size calculations
Cohen’s d was used for effect size calculation, using the differences between 2 means divided by the pooled standard deviations. An effect size from 0.2 to 0.5 was defined as small, from 0.5 to 0.8 as medium, and from 0.8 to infinity as large.25 Results Figure 1 provides an overview of the search strategy. Methodological quality scores
Ten studies were scored for methodological quality. Cohen’s kappa between the scores of the 2 researchers was 0.72, indicating a good agreement. After discussion, a consensus was found for all disagreements. Table 2 presents an overview of the scores of the methodology checklist. One study was excluded because of a methodological score below the cut-off point described in the Methods section.26 In total, 9 studies27-35 were included in this systematic literature study. Seven were true experimental studies,28,30-35 and 2 were pre-experimental studies.27,29 Descriptive analysis
Following the PICO method, Table 3 presents the main characteristics of the included studies.
If possible, effect size calculations (Cohen’s d) were performed and are reported in Table 4. In 2 studies, only the mean values were reported without their standard deviations; as a consequence, no effect size could be calculated for these data.30,34 Study design
In total, 359 stroke patients were included in the various studies: 229 of the participants (70.5% male) received RAGT, and the other 130 were included in the control groups. One hundred sixty-four had left hemiparesis, 148 had right hemiparesis, and 7 had tetraplegia. In one study (n = 40), the side of the hemiparesis was not reported.34 The mean time after stroke varied greatly among the studies (from 2.3 weeks to 48.5 months). The mean age of the participants ranged from 48.11 to 70.35 years. In all true experimental studies, the intervention and control groups were comparable at baseline, with the exception of one study in which a significant difference in age (P < .05) was found between the 2 groups.30 Using a linear regression model, the authors found that age was not related to improvements in gait; therefore, no corrections were made for age.30 Hidler et al30 reported that at 3-month follow-up,7 participants were lost to follow-up (5 in the intervention group and 2 in the control group). Ng, Tong, and Li35 and Tong, Ng, and Li32 reported that after 4 weeks of training, 4 participants in the control group were lost to follow up. Peurala et al28 stated that at 3-month follow-up, 2 participants (1 in the RAGT without FES group and 1 in the control group) were lost to follow-up. All loss to follow-up was for reasons not related to the therapy itself. In the experimental
90
TOPICS IN STROKE REHABILITATION/MAR-APR 2014
After key word search: PubMed: 208 hits Web of knowledge: 347
After reading title and removing duplicates: 60
Exclusion after reading abstract: 47 (children: 1; no effect study: 2; no outcome on balance: 2; RAGT only in comb with FES: 1; upper extremity: 8; no robot: 25; language: 2; reviews and technical papers: 6)
After reading abstract: 13
Exclusion after reading fulltext: 3 (no robot: 1; upper extremity: 1; no outcome on balance: 1)
Finally included: 10
Figure 1. Flowchart search strategy. comb = combination; FES = functional electrostimulation; RAGT = robot-assisted gait training. Table 2.
Methodological quality scores
Evaluation criteria Study question (/2) Study design (/14) Subjects (/8) Intervention (/6) Outcomes (/6) Analysis (/10) Recommendations (/2) Total quality score (/48) a
True experimental. Pre-experimental.
b
Dias et al34a
Hidler et al30a
Peurala et al28a
Ng Tong et al35a et al32a
2 12 5 5 5 8 2
2 10 7 5 6 6 2
2 11 6 4 5 8 2
2 10 6 5 5 8 2
39 (81%)
38 (79%)
38 (79%)
38 (79%)
2 11 6 5 3 8 2 37 (77%)
Westlake et al33a
Fisher et al31a
Conesa et al27b
Wong et al29b
Krishnan et al26b
Mean score
2 10 5 5 5 8 2
2 10 6 4 3 6 2
2 7 4 2 4 7 2
2 8 4 2 5 4 2
2 6 2 2 3 4 2
2 9.5 5 4 4.5 6.5 2
28 (58%)
27 (56%)
21 (44%)
33.5 (70%)
37 (77%)
33 (69%)
n=33; 21 M/12 F Age: 59.9 ± 11.3 y Time post stroke: 110.9 ± 62.5 d Side of hemiplegia: 22 L/11 R
Gait trainer: n=15; 13 M/ 2F Age: 51.2 ± 7.9 y Time post stroke: 2.4 ± 2.6 y Side of hemiplegia: 8 L/7 R Gait trainer + FES: n=15; 13 M/2 F Age: 53.3 ± 8.9 y Time post stroke: 2.6 ± 2.4 y Side of hemiplegia: 9 L/6 R Gait trainer: n=17; 11 M/6 F Age: 66.6 ± 11.3 y Time post stroke: 2.7 ± 1.2 wk Side of hemiplegia: 9 L/8 R Gait trainer + FES: n=15; 10 M/5 F Age: 62 ± 10 y Time post stroke: 2.3 ± 1.1 wk Side of hemiplegia: 9 L/6 R
Hidler et al30 True exp (MQS: 79%)
Peurala et al28 True exp (MQS: 79%)
Ng et al35 True exp (MQS: 79%)
n=20; 16 M/4 F Age: 70.35 ± 7.35 y Time post stroke: 47.10 ± 63.83 mo
Participants in intervention groups
n=21; 13 M/8 F Age: 73.4 ± 11.5 y Time post stroke: 2.5 ± 1.2 wk Side of hemiplegia: 13 L/8 R
n=15; 11 M/4 F Age: 52.3 ± 6.8 y Time post stroke: 4.0 ± 5.8 y Side of hemiplegia: 5 L/10 R
n=30; 18 M/12 F Age: 54.6 ± 9.4 y Time post stroke: 138.9 ± 60.9 d Side of hemiplegia: 13 L/17 R
n=20; 14 M/6 F Age: 68 ± 10.69 y Time post stroke: 48.45 ± 29.51 mo
Participants in control groups
Population
Descriptive analysis of the included studies
Dias et al34 True exp (MQS: 81%)
Table 3.
5×/wk, 3 wk, 15 sessions of 20 min + other PT (55 min 5 ×/wk)
3×/wk, 8 to 10 wk, 24 sessions, 90 min (45 min of effective therapy)
5×/wk, for 5 wk, 40 min (including 20 min of mobilization + muscle training), 25 sessions
Training frequency
Lokomat 1.5 k/h, 40% BWS When sessions were increased, there were improvements in gait speed, decrease in BWS Gait trainer Gait trainer + FES 0 to 2 k/h When sessions were increased, there were improvements in gait speed, decrease in BWS (aiming to support
