Electromechanical Gait Trainers

One fair quality RCT (Peurala et al., 2009) examined the effect of an end-effector gait trainer on functional ambulation in the acute phase of stroke recovery. This fair quality RCT randomized patients to receive (1) gait training using the GT1 device, (2) time-matched overground walking training, or (3) conventional rehabilitation alone. Functional ambulation was measured using the Functional Ambulation Category at post-treatment (3 weeks) and follow-up (6 months). No significant between-group differences were found at either time point.
Note: The end-effector gait training group showed significantly lower perceived exertion during training (measured by the Borg scale) compared to the other groups, and achieved the required 20 minutes of walking per 1-hour session in less time than the overground walking training group, which often required the full 1 hour before achieving 20 minutes of walking.

Conclusion: There is limited evidence (Level 2a) from 1 fair quality RCT that end-effector gait trainers are not more effective than comparison interventions (overground walking training, conventional rehabilitation alone) in improving functional ambulation in the acute phase of stroke recovery.

One fair quality RCT (Peurala et al., 2009) examined the effect of an end-effector gait trainer on mobility in the acute phase of stroke recovery. This fair quality RCT randomized patients to receive (1) gait training using the GT1 device, (2) time-matched overground walking training, or (3) conventional rehabilitation alone. Mobility was measured using the Rivermead Mobility Index and the Rivermead Motor Assessment Scale (RMA – Gross motor function, Lower extremity function and trunk control) at post-treatment (3 weeks) and follow-up (6 months). No significant between-group differences were found on either measure at either time point.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that end-effector gait trainers are not more effective than comparison interventions (overground walking training, conventional rehabilitation alone) in improving mobility in the acute phase of stroke recovery.

One fair quality RCT (Peurala et al., 2009) examined the effect of an end-effector gait trainer on motor function in the acute phase of stroke recovery. This fair quality RCT randomized patients to receive (1) gait training using the GT1 device, (2) time-matched overground walking training, or (3) conventional rehabilitation alone. Motor function was measured using the Modified Motor Assessment Scale (MMAS) at post-treatment (3 weeks) and follow-up (6 months). A significant between-group difference was seen at post-treatment, in favour of end-effector gait training vs. conventional rehabilitation alone. Differences did not remain significant at follow-up. There were no significant differences between end-effector gait training vs. overground walking training.
Note: A significant between-group difference was found at post-treatment in favour of overground walking vs. conventional rehabilitation; differences did not remain significant at follow-up.

Conclusion: There is limited evidence (Level 2a) from 1 fair quality RCT that end-effector gait trainers are more effective, in short-term, than a comparison intervention (conventional rehabilitation) in improving motor function in the acute phase of stroke recovery.
Note: End-effector gait trainers were not more effective than overground walking training.

One fair quality RCT (Peurala et al., 2009) examined the effect of an end-effector gait trainer on walking endurance in the acute phase of stroke recovery. This fair quality RCT randomized patients to receive (1) gait training using the GT1 device, (2) time-matched overground walking training, or (3) conventional rehabilitation alone. Walking endurance was measured using the 6 Minute Walk Test at post-treatment (3 weeks) and follow-up (6 months). A significant difference was found at follow-up, in favour of end-effector gait training vs. overground walking.
Note: Insufficient data was gathered from the conventional rehabilitation group at either time point and no between-group comparisons were made.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that end-effector gait trainers are not more effective than a comparison intervention (overground walking training) in improving walking endurance in the acute phase of stroke recovery.
Note: End-effector gait trainers were more effective than overground walking in the long term.

One fair quality RCT (Peurala et al., 2009) examined the effect of an end-effector gait trainer on walking speed in the acute phase of stroke recovery. This fair quality RCT randomized patients to receive (1) gait training using the GT1 device, (2) time-matched overground walking training, or (3) conventional rehabilitation alone. Walking speed was measured using the 10-meter walking test at post-treatment (3 weeks) and follow-up (6 months). No significant between-group differences were found at either time point.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that end-effector gait trainers are not more effective than comparison interventions (overground walking training, conventional rehabilitation alone) in improving walking speed in the acute phase of stroke recovery.

One high quality RCT (Chang et al., 2012) investigated the effect of exoskeleton gait trainers on cardiopulmonary fitness in the acute phase of stroke recovery. The high quality RCT randomized patients to receive gait training using the Lokomat device or time-matched conventional physical therapy; both groups received additional physical therapy. Cardiopulmonary fitness was measured according to aerobic capacity (peak VO2, respiratory exchange ratio), cardiovascular response (oxygen pulse, peak heart rate, systolic/diastolic blood pressure, rate of perceived exertion) and ventilatory response (minute ventilation, ventilatory efficiency) at post-treatment (2 weeks). There was a significant between-group difference in aerobic capacity only (peak VO2), in favour of exoskeleton gait training vs. conventional physical therapy.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that an exoskeleton gait trainer is not more effective than a comparison intervention (conventional physical therapy) for improving cardiopulmonary fitness in the acute phase of stroke recovery.

One high quality RCT (Chang et al., 2012) investigated the effect of exoskeleton gait trainers on functional ambulation in the acute phase of stroke recovery. The high quality RCT randomized patients to receive gait training using the Lokomat device or time-matched conventional physical therapy; both groups received additional physical therapy. Functional ambulation was measured using the Functional Ambulation Categories at post-treatment (2 weeks). No significant between-group difference was found.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that an exoskeleton gait trainer is not more effective than a comparison intervention (conventional physical therapy) for improving functional ambulation in the acute phase of stroke recovery.

One high quality RCT (Chang et al., 2012) investigated the effect of exoskeleton gait trainers on lower extremity motor function in the acute phase of stroke recovery. The high quality RCT randomized patients to receive gait training using the Lokomat device or time-matched conventional physical therapy; both groups received additional physical therapy. Lower extremity motor function was measured using the Fugl-Meyer Assessment – Lower Extremity score (FMA-LE) at post-treatment (2 weeks). There was a significant between-group difference, in favour of exoskeleton gait training vs. conventional physical therapy.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that an exoskeleton gait trainer is more effective than a comparison intervention (conventional physical therapy) for improving lower extremity motor function in the acute phase of stroke recovery.

One high quality RCT (Chang et al., 2012) investigated the effect of exoskeleton gait trainers on lower extremity motor power in the acute phase of stroke recovery. The high quality RCT randomized patients to receive gait training using the Lokomat device or time-matched conventional physical therapy; both groups received additional physical therapy. Lower extremity motor power was measured using the Motricity Index – Leg score at post-treatment (2 weeks). No significant between-group difference was found.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that an exoskeleton gait trainer is not more effective than a comparison intervention (conventional physical therapy) for improving lower extremity motor power in the acute phase of stroke recovery.

One high quality RCT (Pohl et al., 2007) investigated the effect of end-effector gait trainers on activities of daily living (ADLs) in the subacute phase of stroke recovery. This high quality RCT randomized patients to receive gait training using the GT1 device or time-matched physical therapy. ADLs were measured using the Barthel Index (BI) at post-treatment (4 weeks) and follow-up (6 months). A significant between-group difference in the number of patients who achieved BI scores > 75 was seen at post-treatment, in favour of end-effector gait training vs. physical therapy. This difference did not remain significant at follow-up.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that end-effector gait trainers are more effective, in short-term, than a comparison intervention (time-matched physical therapy) in improving Activities of daily living in the subacute phase of stroke recovery.

One non-randomized study (Iacovelli et al., 2018) examined the effect of end-effector gait trainers on balance in the subacute phase of stroke recovery. This non-randomized controlled trial assigned patients to receive gait training using the G-EO device or conventional gait training. Balance was measured using the Tinetti Scale at post-treatment (20 sessions). No significant between-group difference was found.

Conclusion: There is limited evidence (Level 2b) from one non-randomized study that end-effector gait trainers are not more effective than a comparison intervention (conventional gait training) in improving balance in the subacute phase of stroke recovery.

Two high quality RCTs (Werner et al., 2002; Pohl et al., 2007) and two non-randomized studies (Hesse et al., 2012; Iacovelli et al., 2018) investigated the effect of end-effector gait trainers on functional ambulation in the subacute phase of stroke recovery.

The first high quality cross-over design RCT (Werner et al., 2002) randomized patients to receive gait training using the GT1 device or body-weight supported treadmill training (BWS-TT). Interventions were provided using an A-B-A or B-A-B design, with each block lasting 2 weeks (6 weeks total). Functional ambulation was measured by the Functional Ambulation Category (FAC) at post-treatment (6 weeks) and follow-up (6 months). A significant between-group difference was found at post-treatment, in favour of end-effector gait training vs. BWS-TT; the difference did not remain significant at follow-up.

The second high quality RCT (Pohl et al., 2007) randomized patients to receive gait training using the GT1 device or time-matched physical therapy. Functional ambulation was measured by the FAC at post-treatment (4 weeks) and follow-up (6 months). A significant between-group difference was found at both time points in the number of patients to achieve independent walking (FAC > 4) at post-treatment, in favour of end-effector gait training vs. physical therapy.

The first non-randomized controlled trial (Hesse et al., 2012) assigned non-ambulatory patients to receive gait training using the G-EO device or time-matched physical therapy. Functional ambulation was measured using the FAC at post-treatment (4 weeks) and follow-up (3 months). A significant between-group difference was found at both time points, in favour of end-effector gait training vs. physical therapy.

The second non-randomized controlled trial (Iacovelli et al., 2018) assigned patients to receive gait training using the G-EO device or conventional gait training. Functional ambulation was measured using the FAC and the Walking Handicap Scale at post-treatment (20 sessions). No significant between-group differences were found.

Conclusion: There is strong evidence (Level 1a) from 2 high quality RCTs and one non-randomized study that end-effector gait trainers are more effective than comparison interventions (body-weight supported treadmill training or physical therapy) for improving functional ambulation in the subacute phase of stroke recovery.

One non-randomized study (Iacovelli et al., 2018) examined the effect of end-effector gait trainers on gait parameters in the subacute phase of stroke recovery. This non-randomized controlled trial assigned patients to receive gait training using the G-EO device or conventional gait training. Gait parameters were measured using the SMART0D500 optoelectronic system (stride time, stride length, step length, cadence, velocity, swing velocity, mean velocity) and five measures (step length, swing time, stance time, double support time, intra-limb ratio of swing: stance time) were used to calculate the symmetry index (symmetry ratio, symmetry index, gait asymmetry, symmetry angle) at post-treatment (20 sessions). Significant between-group differences were found in only two gait parameters (symmetry ratio – step length, symmetry angle – step length), in favour of end-effector gait training vs. conventional gait training.

Conclusion: There is limited evidence (Level 2b) from one non-randomized study that end-effector gait trainers are not more effective than a comparison intervention (conventional gait training) for improving gait parameters in the subacute phase of stroke recovery.

Two high quality RCTs (Werner et al., 2002; Pohl et al., 2007) and two non-randomized studies (Hesse et al., 2012; Iacovelli et al., 2018) investigated the effect of end-effector gait trainers on mobility in patients with subacute stroke.

The first high quality cross-over design RCT (Werner et al., 2002) randomized patients to receive gait training using the GT1 device or body-weight supported treadmill training (BWS-TT). Interventions were provided using an A-B-A or B-A-B design, with each block lasting 2 weeks (6 weeks total). Mobility was measured using the Rivermead Motor Assessment (RMA – Gross function, Trunk and leg subscales) at post-treatment (6 weeks). No significant between-group differences were found.

The second high quality RCT (Pohl et al., 2007) randomized patients to receive gait training using the GT1 device or time-matched physical therapy. Mobility was measured using the Rivermead Mobility Index (RMI) at post-treatment (4 weeks) and follow-up (6 months). A significant between-group difference was found at post-treatment in favour of end-effector gait training vs. physical therapy. Differences did not remain significant at follow-up.

The first non-randomized controlled trial (Hesse et al., 2012) assigned non-ambulatory patients to receive gait training using the G-EO device or time-matched physical therapy. Mobility was measured using the RMI at post-treatment (4 weeks) and follow-up (3 months). A significant between-group difference was found at post-treatment in favour of end-effector gait training vs. physical therapy. Differences did not remain significant at follow-up.

The second non-randomized controlled trial (Iacovelli et al., 2018) assigned patients to receive gait training using the G-EO device or conventional gait training. Mobility was measured using the Timed Up and Go (TUG) test and the Trunk Control Test at post-treatment (20 sessions). A significant between-group difference was found in one measure of mobility (TUG) in favour of end-effector gait training vs. conventional gait training.

Conclusion: There is conflicting evidence (Level 4) regarding the effect of end-effector gait trainers on mobility in the subacute phase of stroke recovery. One high quality RCT and two non-randomized studies found that end-effector gait trainers are more effective than comparison interventions (physical therapy, conventional gait training); a second high quality RCT found no significant difference compared with body-weight supported treadmill training.
Note: Differences in results may relate to the variation in outcome measures used.

One non-randomized study (Iacovelli et al., 2018) examined the effect of end-effector gait trainers on lower extremity motor function in the subacute phase of stroke recovery. This non-randomized controlled trial assigned patients to receive gait training using the G-EO device or conventional gait training. Lower extremity motor function was measured using the Fugl-Meyer Assessment – Lower Extremity at post-treatment (20 sessions). No significant between-group difference was found.

Conclusion: There is limited evidence (Level 2b) from one non-randomized study that end-effector gait trainers are not more effective than a comparison intervention (conventional gait training) for improving lower extremity motor function in the subacute phase of stroke recovery.

One high quality RCT (Pohl et al., 2007) and two non-randomized studies (Hesse et al., 2012; Iacovelli et al., 2018) examined the effect of end-effector gait trainers on lower extremity muscle strength in the subacute phase of stroke recovery.

The high quality RCT (Pohl et al., 2007) randomized patients to receive gait training using the GT1 device or time-matched physical therapy. Lower extremity muscle strength was measured using the Motricity Index (MI) and post-treatment (4 weeks) and follow-up (6 months). A significant between-group difference was seen at post-treatment in favour of end-effector gait training vs. physical therapy. Differences did not remain significant at follow-up.

The first non-randomized controlled trial (Hesse et al., 2012) assigned non-ambulatory patients to receive gait training using the G-EO device or time-matched physical therapy. Lower extremity muscle strength was measured using the MI at post-treatment (4 weeks) and follow-up (3 months). A significant between-group difference was found at both time points in favour of end-effector gait training vs. physical therapy.

The second non-randomized controlled trial (Iacovelli et al., 2018) assigned patients to receive gait training using the G-EO device or conventional gait training. Lower extremity muscle strength was measured using the MI and the Medical Research Council Scale (MRC Scale – Hip extension, Knee flexion, Ankle flexion) at post-treatment (20 sessions). Significant between-group differences were found on two measures of muscle strength (MRC scale – Hip extension, Ankle flexion), in favour of end-effector gait training vs. conventional gait training.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and two non-randomized studies that end-effector gait trainers are more effective than comparison interventions (time-matched physical therapy, conventional gait training) for improving lower extremity muscle strength in the subacute phase of stroke recovery.

One high quality RCT (Werner et al., 2002) and two non-randomized studies (Hesse et al., 2012; Iacovelli et al., 2018) examined the effect of end-effector gait trainers on lower extremity muscle tone/spasticity in the subacute phase of stroke recovery.

The high quality cross-over design RCT (Werner et al., 2002) randomized patients to receive gait training using the GT1 device or body-weight supported treadmill training (BWS-TT). Interventions were provided using an A-B-A or B-A-B design, with each block lasting 2 weeks (6 weeks total). Spasticity was measured by the Modified Ashworth Scale at post-treatment (6 weeks). No significant between-group difference was found.

The first non-randomized controlled trial (Hesse et al., 2012) assigned non-ambulatory patients to receive gait training using the G-EO device or time-matched physical therapy. Lower extremity muscle tone was measured using the Resistance to Passive Movement Scale at post-treatment (4 weeks) and follow-up (3 months). No significant between-group difference was found at either time point.

The second non-randomized controlled trial (Iacovelli et al., 2018) assigned patients to receive gait training using the G-EO device or conventional gait training. Lower extremity spasticity was measured using the Ashworth Scale (Total score, Hip, Knee) at post-treatment (20 sessions). Significant between-group differences were found on all measures of Ahsworth Scale, in favour of end-effector gait training vs. conventional gait training.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and one non-randomized study that end-effector gait trainers are not more effective than comparison interventions (body-weight supported treadmill training, time-matched physical therapy) in improving lower extremity muscle tone/spasticity in the subacute phase of stroke recovery.
Note: However, a second non-randomized study found that end-effector gait trainers were more effective than conventional gait training.

One non-randomized study (Iacovelli et al., 2018) examined the effect of end-effector gait trainers on lower extremity range of motion in the subacute phase of stroke recovery. This non-randomized controlled trial assigned patients to receive gait training using the G-EO device or conventional gait training. Lower extremity range of motion (Hip, Knee, Ankle) was measured in the sagittal plane at post-treatment (20 sessions). No significant between-group differences were found.

Conclusion: There is limited evidence (Level 2b) from one non-randomized study that end-effector gait trainers are not more effective than a comparison intervention (conventional gait training) for improving lower extremity range of motion in the subacute phase of stroke recovery.

One high quality RCT (Pohl et al., 2007) and one non-randomized study (Iacovelli et al., 2018) examined the effect of end-effector gait trainers on walking endurance in the subacute phase of stroke recovery.

The high quality RCT (Pohl et al., 2007) randomized patients to receive gait training using the GT1 device or time-matched physical therapy. Walking endurance was measured using the 6 Minute Walk Test (6MWT) at post-treatment (4 weeks) and follow-up (6 months). A significant between-group difference was seen at post-treatment in favour of end-effector gait training vs. physical therapy. Results did not remain significant at follow-up.

The non-randomized controlled trial (Iacovelli et al., 2018) assigned patients to receive gait training using the G-EO device or conventional gait training. Walking endurance was measured using the 6MWT at post-treatment (20 sessions). A significant between-group difference was found in favour of end-effector gait training vs. conventional gait training.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and one non-randomized study that end-effector gait trainersare more effective than comparison interventions (physical therapy, conventional gait training) for improving walking endurance in the subacute phase of stroke recovery.

Two high quality RCTs (Werner et al., 2002; Pohl et al., 2007) and two non-randomized studies (Hesse et al., 2012; Iacovelli et al., 2018) investigated the effect of end-effector gait trainers on walking speed in the subacute phase of stroke recovery.

The first high quality cross-over design RCT (Werner et al., 2002) randomized patients to receive gait training using the GT1 device or Body-Weight Supported Treadmill Training (BWS-TT) using an A-B-A or B-A-B format, with each block lasting 2 weeks (6 weeks total). Walking speed was measured using the 10-meter walking test each week for 6 weeks (post-treatment). No significant between-group difference was found.

The second high quality RCT (Pohl et al., 2007) randomized patients to receive gait training using the GT1 device or time-matched physical therapy. Walking speed was measured using the 10-meter walking test at post-treatment (4 weeks) and follow-up (6 months). There was a significant between-group difference at post-treatment in favour of end-effector gait training vs. physical therapy. Between-group differences did not remain significant at follow-up.

The first non-randomized controlled trial (Hesse et al., 2012) assigned non-ambulatory patients to receive gait training using the G-EO device or time-matched physical therapy. Walking speed was measured using the 10-meter walking test at post-treatment (4 weeks) and follow-up (3 months). A significant between-group difference was found at post-treatment in favour of end-effector gait training vs. physical therapy. Differences did not remain significant at follow-up.

The second non-randomized controlled trial (Iacovelli et al., 2018) assigned patients to receive gait training using the G-EO device or conventional gait training. Walking speed was measured using the 10-meter walking test at post-treatment (20 sessions). A significant between-group difference was found in favour of end-effector gait training vs. conventional gait training.

Conclusion: There is conflicting evidence (Level 4) regarding the effect of end-effector gait trainers on walking speed in the subacute phase of stroke recovery. One high quality RCT and two non-randomized studies found that end-effector gait trainers are more effective than comparison interventions (physical therapy, conventional gait training), whereas a second high quality RCT found no significant difference between end-effector gait trainers and Body-Weight Supported Treadmill Training.

One high quality RCT (Husemann et al., 2007), two fair quality RCT (Hidler et al., 2009; Han et al., 2016) and one non-randomized study (Chung, 2017) investigated the effect of exoskeleton gait trainers on ADLs or IADLs in the subacute phase of stroke recovery.

The high quality RCT (Husemann et al., 2007) randomized patients to receive gait training using the Lokomat device or conventional physical therapy. ADLs were measured by the Barthel Index (BI) at post-treatment (4 weeks). No significant between-group difference was found.

The first fair quality RCT (Hidler et al., 2009) randomized patients to receive gait training using the Lokomat device or time-matched conventional gait training. IADLs were measured using the Frenchay Activities Index at mid-treatment (12 sessions), post-treatment (24 sessions) and follow-up (3 months). No significant between-group difference was found at any timepoint.

The second fair quality RCT (Han et al., 2016) randomized patients to receive gait training using the Lokomat device or conventional physical therapy; both groups received additional physical therapy and occupational therapy. ADLs were measured by the Korean modified Barthel Index at post-treatment (4 weeks). No significant between-group difference was found.

The non-randomized case-controlled study (Chung, 2017) provided patients with gait training using the Lokomat device and physical therapy or time-matched physical therapy. ADLs were measured by the modified BI at discharge (approximately 5 weeks). No significant between-group difference in change scores was found.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT, two fair quality RCTs and one non-randomized study that exoskeleton gait trainers are not more effective than comparison interventions (conventional physical therapy, conventional gait training) for improving ADLs or IADLs in the subacute phase of stroke recovery.

One high quality RCT (Taveggia et al., 2016), three fair quality RCTs (Hidler et al., 2009; van Nunen et al., 2015; Han et al., 2016) and one non-randomized study (Chung, 2017) investigated the effect of exoskeleton gait trainers on balance in the subacute phase of stroke recovery.

The high quality RCT (Taveggia et al., 2016) randomized patients to receive gait training using the Lokomat device or time-matched conventional physical therapy for gait retraining; both groups received additional physical therapy. Balance was measured by the Tinetti Balance Scale at post-treatment (5 weeks) and follow-up (3 months). No significant between-group difference was found at either timepoint.

The first fair quality RCT (Hidler et al., 2009) randomized patients to receive gait training using the Lokomat device or time-matched conventional gait training. Balance was measured using the Berg Balance Scale (BBS) at mid-treatment (12 sessions), post-treatment (24 sessions) and follow-up (3 months). No significant between-group difference was found at any timepoint.

The second fair quality RCT (van Nunen et al., 2015) randomized patients to receive gait training using the Lokomat device or dose-matched overground gait training; both groups received additional physical therapy. Balance was measured by the BBS at post-treatment (10 weeks) and follow-up (week 24, week 36). No significant between-group difference was found at any timepoint.

The third fair quality RCT (Han et al., 2016) randomized patients to receive gait training using the Lokomat device or conventional physical therapy; both groups received additional physical therapy and occupational therapy. Balance was measured by the BBS at post-treatment (4 weeks). No significant between-group difference was found.

The non-randomized case-controlled study (Chung, 2017) provided patients with gait training using the Lokomat device and physical therapy or time-matched physical therapy. Balance was measured by the BBS at baseline and at discharge (approximately 5 weeks). A significant between-group difference in change scores from baseline to discharge was found, in favour of exoskeleton gait training + physical therapy vs. physical therapy alone.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and three fair quality RCTs that exoskeleton gait trainers are not more effective than comparison interventions (conventional physical therapy, conventional gait training, overground gait training) for improving balance in the subacute phase of stroke recovery.
Note: The non-randomized study found that the exoskeleton gait trainer was more effective than time-matched physical therapy.

One high quality RCT (Husemann et al., 2007), three fair quality RCTs (Hidler et al., 2009; van Nunen et al., 2015; Han et al., 2016) and one non-randomized study (Chung, 2017) investigated the effect of exoskeleton gait trainers on functional ambulation in the subacute phase of stroke recovery.

The high quality RCT (Husemann et al., 2007) randomized patients to receive gait training using the Lokomat device or conventional physical therapy. Functional ambulation was measured by the Functional Ambulation Category (FAC) at post-treatment (4 weeks). No significant between-group difference was found.

The first fair quality RCT (Hidler et al., 2009) randomized patients to receive gait training using the Lokomat device or time-matched conventional gait training. Functional ambulation was measured using the FAC at mid-treatment (12 sessions), post-treatment (24 sessions) and follow-up (3 months). No significant between-group difference was found at any timepoint.

The second fair quality RCT (van Nunen et al., 2015) randomized patients to receive gait training using the Lokomat device or dose-matched overground gait training; both groups received additional physical therapy. Functional ambulation was measured by the FAC at post-treatment (10 weeks) and follow-up (week 24, week 36). No significant between-group difference was found at any timepoint.

The third fair quality RCT (Han et al., 2016) randomized patients to receive gait training using the Lokomat device or conventional physical therapy; both groups received additional physical therapy and occupational therapy. Functional ambulation was measured by the FAC at post-treatment (4 weeks). No significant between-group difference was found.

The non-randomized case-controlled study (Chung, 2017) provided patients with gait training using the Lokomat device and physical therapy or time-matched physical therapy. Functional ambulation was measured by the modified FAC at baseline and at discharge (approximately 5 weeks). A significant between-group difference in change scores from baseline to discharge was found, in favour of exoskeleton gait training + physical therapy vs. physical therapy alone.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and three fair quality RCTs that exoskeleton gait trainers are not more effective than comparison interventions (conventional physical therapy, conventional gait training, overground gait training) for improving functional ambulation in the subacute phase of stroke recovery.
Note: The non-randomized study found that the exoskeleton gait trainer was more effective than time-matched physical therapy.

One high quality RCT (Taveggia et al., 2016) investigated the effect of an exoskeleton gait trainer on functional independence in the subacute phase of stroke recovery. This high quality RCT randomized patients to receive gait training using the Lokomat device or time-matched conventional physical therapy for gait retraining; both groups received additional physical therapy. Functional independence was measured by the Functional Independence Measure at post-treatment (5 weeks) and follow-up (3 months). No significant between-group difference was found at either timepoint.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that an exoskeleton gait trainer is not more effective than a comparison intervention (conventional physical therapy) for improving functional independence in the subacute phase of stroke recovery.

One high quality RCT (Husemann et al., 2007) and one fair quality RCT (Hidler et al., 2009) investigated the effect of exoskeleton gait trainers on gait parameters in the subacute phase of stroke recovery.

The high quality RCT (Husemann et al., 2007) randomized patients to receive gait training using the Lokomat device or conventional physical therapy. Gait parameters were measured by the Parotec system (Cadence, Stride duration, Stance duration – affected/unaffected leg, Single support time – affected/unaffected leg) at post-treatment (4 weeks). A significant between-group difference in one measure (Single support time – affected leg) was found, in favour of exoskeleton gait training vs. conventional physical therapy.

The fair quality RCT (Hidler et al., 2009) randomized patients to receive gait training using the Lokomat device or time-matched conventional gait training. One gait parameter was measured using the GAITRite system (Cadence) at mid-treatment (12 sessions), post-treatment (24 sessions) and follow-up (3 months). No significant between-group difference was found at any timepoint.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and one fair quality RCT that exoskeleton gait trainers are not more effective than comparison interventions (conventional physical therapy, conventional gait training) for improving gait parameters in the subacute phase of stroke recovery.

One high quality RCT (Taveggia et al., 2016) and two fair quality RCTs (Hidler et al., 2009; van Nunen et al., 2015) investigated the effect of exoskeleton gait trainers on health related quality of life (HRQoL) in the subacute phase of stroke recovery.

The high quality RCT (Taveggia et al., 2016) randomized patients to receive gait training using the Lokomat device or time-matched conventional physical therapy for gait retraining; both groups received additional physical therapy. HRQoL was measured by the Medical Outcomes Study Short Form 36 (SF-36) at post-treatment (5 weeks) and follow-up (3 months). No significant between-group difference was found at either timepoint.

The first fair quality RCT (Hidler et al., 2009) randomized patients to receive gait training using the Lokomat device or time-matched conventional gait training. HRQoL was measured using the SF-36 at mid-treatment (12 sessions), post-treatment (24 sessions) and follow-up (3 months). No significant between-group difference was found at any timepoint.

The second fair quality RCT (van Nunen et al., 2015) randomized patients to receive gait training using the Lokomat device or dose-matched overground gait training; both groups received additional physical therapy. HRQoL was measured by the SF-36 (General health, Social functioning scores) and the Stroke Impact Scale (SIS 3.0 – Activities of Daily Living, Mobility scores) at post-treatment (10 weeks) and follow-up (week 24, week 36). No significant between-group differences were found on either measure at any timepoint.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and two fair quality RCTs that exoskeleton gait trainers are not more effective than comparison interventions (conventional physical therapy, conventional gait training, overground gait training) for improving quality of life in the subacute phase of stroke recovery.

Two fair quality RCTs (Hidler et al., 2009; van Nunen et al., 2015) and one non-randomized study (Chung, 2017) investigated the effect of exoskeleton gait trainers on mobility in the subacute phase of stroke recovery.

The first fair quality RCT (Hidler et al., 2009) randomized patients to receive gait training using the Lokomat device or time-matched conventional gait training. Mobility was measured using the Rivermead Mobility Index (RMI) at mid-treatment (12 sessions), post-treatment (24 sessions) and follow-up (3 months). No significant between-group difference was found at any timepoint.

The second fair quality RCT (van Nunen et al., 2015) randomized patients to receive gait training using the Lokomat device or dose-matched overground gait training; both groups received additional physical therapy. Mobility was measured by the RMI at post-treatment (10 weeks) and follow-up (week 24, week 36); the Timed Up and Go test was also used with patients with a Functional Ambulation Category of or greater than 3. No significant between-group differences were found on either measure at any timepoint.

The non-randomized case-controlled study (Chung, 2017) provided patients with gait training using the Lokomat device and physical therapy or time-matched physical therapy. Mobility was measured by the modified RMI at baseline and at discharge (approximately 5 weeks). A significant between-group difference in change scores from baseline to discharge was found, in favour of exoskeleton gait training + physical therapy vs. physical therapy alone.

Conclusion: There is limited evidence (Level 2a) from two fair quality RCTs that exoskeleton gait trainers are not more effective than comparison interventions (conventional gait training, overground gait training) for improving mobility in the subacute phase of stroke recovery.
Note: A non-randomized study found that the exoskeleton gait trainer was more effective than physical therapy alone.

Three fair quality RCTs (Hidler et al., 2009; van Nunen et al., 2015; Han et al., 2016) investigated the effect of exoskeleton gait trainers on lower extremity motor function in the subacute phase of stroke recovery.

The first fair quality RCT (Hidler et al., 2009) randomized patients to receive gait training using the Lokomat device or time-matched conventional gait training. Lower extremity motor function was measured using the Motor Assessment Scale at mid-treatment (12 sessions), post-treatment (24 sessions) and follow-up (3 months). No significant between-group difference was found at any timepoint.

The second fair quality RCT (van Nunen et al., 2015) randomized patients to receive gait training using the Lokomat device or dose-matched overground gait training; both groups received additional physical therapy. Lower extremity motor function was measured by the Fugl-Meyer Assessment – Lower Extremity (FMA-LE) at post-treatment (10 weeks) and follow-up (week 24, week 36). No significant between-group difference was found at any timepoint.

The third fair quality RCT (Han et al., 2016) randomized patients to receive gait training using the Lokomat device or conventional physical therapy; both groups received additional physical therapy and occupational therapy. Lower extremity motor function was measured by the FMA-LE at post-treatment (4 weeks). No significant between-group difference was found.

Conclusion: There is limited evidence (Level 2a) from three fair quality RCTs that exoskeleton gait trainers are not more effective than comparison interventions (conventional gait training, overground gait training, conventional physical therapy) for improving lower extremity motor function in the subacute phase of stroke recovery.

One high quality RCT (Husemann et al., 2007) and one fair quality RCT (van Nunen et al., 2015) investigated the effect of exoskeleton gait trainers on lower extremity muscle strength in the subacute phase of stroke recovery.

The high quality RCT (Husemann et al., 2007) randomized patients to receive gait training using the Lokomat device or conventional physical therapy. Muscle power was measured by the Motricity Index at post-treatment (4 weeks). No significant between-group difference was found.

The fair quality RCT (van Nunen et al., 2015) randomized patients to receive gait training using the Lokomat device or dose-matched overground gait training; both groups received additional physical therapy. Muscle strength was measured according to maximal voluntary isometric torque of bilateral knee extensors and flexors at post-treatment (10 weeks) and follow-up (week 24, week 36). No significant between-group difference was found at any timepoint.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and one fair quality RCT that exoskeleton gait trainers are not more effective than comparison interventions (conventional physical therapy, overground gait training) for improving lower extremity muscle strength in the subacute phase of stroke recovery.

One high quality RCT (Husemann et al., 2007) investigated the effect of an exoskeleton gait trainer on spasticity in the subacute phase of stroke recovery. The high quality RCT randomized patients to receive gait training using the Lokomat device or conventional physical therapy. Spasticity was measured by the Modified Ashworth Scale at post-treatment (4 weeks). No significant between-group difference was found.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that an exoskeleton gait trainer is not more effective than a comparison intervention (conventional physical therapy) for reducing spasticity in the subacute phase of stroke recovery.

One fair quality RCT (van Nunen et al., 2015) investigated the effect of exoskeleton gait trainers on stroke impact the subacute phase of stroke recovery. The fair quality RCT randomized patients to receive gait training using the Lokomat device or dose-matched overground gait training; both groups received additional physical therapy. Stroke impact was measured by the Stroke Impact Scale (SIS 3.0 – Activities of Daily Living, Mobility scores) at post-treatment (10 weeks) and follow-up (week 24, week 36). No significant between-group difference was found at any time point.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that exoskeleton gait trainers are not more effective than a comparison intervention (overground gait training) for reducing the impact of stroke in the subacute phase of stroke recovery.

One fair quality RCT (Hidler et al., 2009) investigated the effect of an exoskeleton gait trainer on stroke severity in the subacute phase of stroke recovery. The fair quality RCT randomized patients to receive gait training using the Lokomat device or time-matched conventional gait training. Stroke severity was measured using the National Institute of Health Stroke Scale (NIHSS) at mid-treatment (12 sessions), post-treatment (24 sessions) and follow-up (3 months). No significant between-group difference was found at any timepoint.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that an exoskeleton gait trainer is not more effective than a comparison intervention (conventional gait training) for reducing stroke severity in the subacute phase of stroke recovery.

One high quality RCT (Taveggia et al., 2016) and one fair quality RCT (Hidler et al., 2009) investigated the effect of exoskeleton gait trainers on walking endurance in the subacute phase of stroke recovery.

The high quality RCT (Taveggia et al., 2016) randomized patients to receive gait training using the Lokomat device or time-matched conventional physical therapy for gait retraining; both groups received additional physical therapy. Walking endurance was measured by the 6 Minute Walk Test (6MWT) at post-treatment (5 weeks) and follow-up (3 months). No significant between-group difference was found at either timepoint.

The fair quality RCT (Hidler et al., 2009) randomized patients to receive gait training using the Lokomat device or time-matched conventional gait training. Walking endurance was measured using the 6MWT at mid-treatment (12 sessions), post-treatment (24 sessions) and follow-up (3 months). A significant between-group difference was found at mid-treatment and post-treatment, in favour of conventional gait training vs. exoskeleton gait training. Differences did not remain significant at follow-up.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and one fair quality RCT that exoskeleton gait trainers are not more effective than comparison interventions (conventional physical therapy, conventional gait training) for improving walking endurance in the subacute phase of stroke recovery.
Note: The fair quality RCT found that conventional gait training was more effective than exoskeleton gait training.

Two high quality RCTs (Husemann et al., 2007; Taveggia et al., 2016) and two fair quality RCTs (Hidler et al., 2009; van Nunen et al., 2015) investigated the effect of exoskeleton gait trainers on walking speed in the subacute phase of stroke recovery.

The first high quality RCT (Husemann et al., 2007) randomized patients to receive gait training using the Lokomat device or conventional physical therapy. Walking speed was measured by the 10-meter walking test at post-treatment (4 weeks). No significant between-group difference was found.

The second high quality RCT (Taveggia et al., 2016) randomized patients to receive gait training using the Lokomat device or time-matched conventional physical therapy for gait retraining; both groups received additional physical therapy. Walking speed was measured by the 10-meter walking test at post-treatment (5 weeks) and follow-up (3 months). No significant between-group difference was found at either timepoint.

The first fair quality RCT (Hidler et al., 2009) randomized patients to receive gait training using the Lokomat device or time-matched conventional gait training. Walking speed was measured using the 5 meter walking test at mid-treatment (12 sessions), post-treatment (24 sessions) and follow-up (3 months). A significant between-group difference was found at all timepoints, in favour of conventional gait training vs. exoskeleton gait training.

The second fair quality RCT (van Nunen et al., 2015) randomized patients to receive gait training using the Lokomat device, or dose-matched overground gait training; both groups received additional physical therapy. Walking speed was measured by the 10-meter walking test at post-treatment (10 weeks) and follow-up (week 24, week 36). No significant between-group difference was found at any timepoint.

Conclusion: There is strong evidence (Level 1a) from two high quality RCTs and two fair quality RCTs that exoskeleton gait trainers are not more effective than comparison interventions (conventional physical therapy, conventional gait training, overground gait training) for improving walking speed in the subacute phase of stroke recovery.
Note: One fair quality RCT found that conventional gait training was more effective than exoskeleton gait training.

One fair quality RCT (Dias et al., 2007) investigated the effect of end-effector gait trainers on Activities of daily living (ADLs) in patients with chronic stroke. The fair quality RCT randomized patients to receive gait training using the GT1 device or time-matched conventional rehabilitation. ADLs were measured using the Barthel Index (BI) at post-treatment (5 weeks) and follow-up (3 months). No significant between-group difference was found at either time point.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that end-effector gait trainers are not more effective than a comparison intervention (conventional rehabilitation) for improving Activities of daily living in the chronic phase of stroke recovery.

One high quality RCT (Peurala et al., 2005) and one fair quality RCT (Dias et al., 2007) investigated the effect of end-effector gait trainers on balance in the chronic phase of stroke recovery.

The high quality RCT (Peurala et al., 2005) randomized patients to receive (1) gait training using the GT1 device, (2) gait training + Functional Electrical Stimulation (GT1+FES), or (3) overground walking training. Postural sway was measured using a force plate at mid-treatment (2 weeks), post-treatment (3 weeks) and follow-up (6 months). No significant between-group differences were found at any time point.

The fair quality RCT (Dias et al., 2007) randomized patients to receive gait training using the GT1 device or time-matched conventional rehabilitation. Balance was measured using the Toulouse Motor Scale (Balance: items 1-10; items 11-20; total), Berg Balance Scale (BBS) and the Step Test at post-treatment (5 weeks) and follow-up (3 months). No significant between-group differences were found on either measure at either time point.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and one fair quality RCT that end-effector gait trainers are not more effective than comparison interventions (overground walking training, conventional rehabilitation) for improving balance in the chronic phase of stroke recovery.
Note: The high quality RCT also found that GT1+FES is not more effective than overground walking training for improving balance in the chronic phase of stroke recovery. There was no significant difference between end-effector gait training with/without FES.

One high quality RCT (Geroin et al., 2011), one fair quality RCT (Dias et al., 2007) and one fair non-randomized study (Park et al., 2015) examined the effect of end-effector gait trainers on functional ambulation in the chronic phase of stroke recovery.

The high quality RCT (Geroin et al., 2011) randomized patients to receive (1) gait training using the GT1 device + sham stimulation (GT1 + sham stimulation), (2) gait training + transcranial direct current stimulation (GT1+tDCS), or (3) conventional overground walking exercises. Functional ambulation was measured using the Functional Ambulation Category (FAC) at post-treatment (2 weeks) and follow-up (4 weeks). A significant between-group difference was found at both time points in favour of GT1 + sham stimulation vs. conventional walking exercises.
Note: A significant between-group difference was found in favour of GT1+tDCS vs. conventional walking exercises at both time points. No significant difference was found between GT1 + sham stimulation vs. GT1+tDCS.

The fair quality RCT (Dias et al., 2007) randomized patients to receive gait training using the GT1 device or time-matched conventional rehabilitation. Functional ambulation was measured using the FAC at post-treatment (5 weeks) and follow-up (3 months). No significant between-group difference was found at either time point.

The fair non-randomized controlled trial (Park et al., 2015) assigned patients to receive gait training using the GT2 device or conventional overground gait training. Functional ambulation was measured using the FAC at post-treatment (4 weeks). No significant between-group difference was found.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that end-effector gait trainers are more effective than a comparison intervention (conventional overground walking exercises) in improving functional ambulation in the chronic phase of stroke recovery. However, one fair quality RCT and fair one non-randomized study found that end-effector gait trainers are not more effective than comparison interventions (conventional rehabilitation, overground gait training).
Note: The high quality RCT also found that GT1+tDCS was more effective than conventional overground walking exercises. There was no significant difference between end-effector gait training with/without tDCS.

One high quality RCT (Peurala et al., 2005) investigated the effect of end-effector gait trainers on functional independence in patients with chronic stroke. This high quality RCT randomized patients to receive (1) gait training using the GT1 device, (2) gait training + Functional Electrical Stimulation (GT1+FES), or (3) overground walking training. Functional independence was measured using the Functional Independence Measure at mid-treatment (2 weeks), post-treatment (3 weeks) and follow-up (6 months). No significant between-group differences were found at any time point.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that end-effector gait trainers are not more effective than a comparison intervention (overground walking training) for improving functional independence in the chronic phase of stroke recovery.
Note: This high quality RCT found that GT1+FES was not more effective than overground walking training. There was no significant difference between end-effector gait training with/without FES.

One high quality RCT (Geroin et al., 2011) and one fair non-randomized study (Park et al., 2015) examined the effect of end-effector gait trainers on gait parameters in the chronic phase of stroke recovery.

The high quality RCT (Geroin et al., 2011) randomized patients to receive (1) gait training using the GT1 device + sham stimulation (GT1 + sham stimulation), (2) gait training + transcranial direct current stimulation (GT1+tDCS), or (3) conventional overground walking exercises. Gait parameters were measured using the GAITRite system (Cadence, Temporal symmetry ratio of swing time to stance phase, Single to double support duration ratio) at post-treatment (2 weeks) and follow-up (4 weeks). Significant between-group differences were found on all gait parameters at both time points, in favour of GT1 + sham stimulation vs. conventional walking exercises.
Note: Significant between-group differences were found on all gait parameters at both time points in favour of GT1+tDCS vs. conventional walking exercises. No significant differences were found between GT1 + sham stimulation vs. GT1+tDCS.

The fair non-randomized controlled trial (Park et al., 2015) assigned patients to receive gait training using the GT2 device or conventional overground gait training. Spatiotemporal gait parameters were measured using the GAITRite system (Walking speed, Walking cycle, Stance phase and stride length of affected side, Symmetry index of stance phase and stride length) at post-treatment (4 weeks). No significant between-group differences were found on either measure.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that end-effector gait trainers (+ sham stimulation) are more effective than a comparison intervention (conventional overground walking exercises) for improving gait parameters in the chronic phase of stroke recovery.
Note: The high quality RCT also found that GT1+tDCS was more effective than conventional overground walking exercises for improving gait parameters. There was no significant difference between end-effector gait training with/without tDCS.
Note: A fair non-randomized study found that end-effector gait training was not more effective than conventional overground gait training.

One high quality RCT (Geroin et al., 2011) and one fair quality RCT (Dias et al., 2007) investigated the effect of end-effector gait trainers on mobility in the chronic phase of stroke recovery.

The high quality RCT (Geroin et al., 2011) randomized patients to receive (1) gait training using the GT1 device + sham stimulation (GT1 + sham stimulation), (2) gait training + transcranial direct current stimulation (GT1+tDCS), or (3) conventional overground walking exercises. Mobility was measured using the Rivermead Mobility Index (RMI) at post-treatment (2 weeks) and follow-up (4 weeks). A significant between-group difference was found at both time points in favour of GT1 + sham stimulation vs. conventional walking exercises.
Note: A significant between-group difference was found at both time points in favour of GT1+tDCS vs. conventional walking exercises. No significant difference was found between GT1 + sham stimulation vs. GT1+tDCS.

The fair quality RCT (Dias et al., 2007) randomized patients to receive gait training using the GT1 device or time-matched conventional rehabilitation. Mobility was measured using the RMI and the Timed Up and Go test at post-treatment (5 weeks) and follow-up (3 months). No significant between-group differences were found on either measure at either time point.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that end-effector gait trainers (+ sham stimulation) are more effective than a comparison intervention (conventional overground walking exercises) for improving mobility in the chronic phase of stroke recovery.
Note: However, one fair quality RCT found that end-effector gait trainers are not more effective than conventional gait training.
Note: The high quality RCT found that GT1+tDCS is more effective than conventional walking exercises. There is no significant difference between end-effector gait training with/without tDCS.

One high quality RCT (Peurala et al., 2005) and one fair quality RCT (Dias et al., 2007) investigated the effect of end-effector gait trainers on motor function in the chronic phase of stroke recovery.

The high quality RCT (Peurala et al., 2005) randomized patients to receive (1) gait training using the GT1 device, (2) gait trainer + Functional Electrical Stimulation (GT1+FES) group, or (3) overground walking training. Motor function was measured using the Modified Motor Assessment Scale at mid-treatment (2 weeks), post-treatment (3 weeks) and follow-up (6 months). No significant differences were found at any time point.

The fair quality RCT (Dias et al., 2007) randomized patients to receive gait training using the GT1 device or time-matched conventional rehabilitation. Motor function was measured using the Fugl-Meyer Stroke Scale at post-treatment (5 weeks) and follow-up (3 months). No significant between-group difference was found at either time point.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and one fair quality RCT that end-effector gait trainers are not more effective than comparison interventions (overground walking training, conventional rehabilitation) for improving motor function in the chronic phase of stroke recovery.
Note: The high quality RCT also found that GT1+FES was not more effective than overground walking training. There was no significant difference between end-effector gait training with/without FES.

One high quality RCT (Geroin et al., 2011) and one fair quality RCT (Dias et al., 2007) investigated the effect of end-effector gait trainers on lower extremity muscle strength in the chronic phase of stroke recovery.

The high quality RCT (Geroin et al., 2011) randomized patients to receive (1) gait training using the GT1 device + sham stimulation (GT1 + sham stimulation), (2) gait training + transcranial direct current stimulation (GT1+tDCS), or (3) conventional overground walking exercises. Muscle strength was measured using the Motricity Index (MI – Leg score) at post-treatment (2 weeks) and follow-up (4 weeks). A significant between-group difference was found at both time points in favour of GT1 + sham stimulation vs. conventional walking exercises.
Note: A significant between-group difference was found at both time points in favour of GT1+tDCS vs. conventional walking exercises. No significant difference was found between GT1 + sham stimulation vs. GT1+tDCS.

The fair quality RCT (Dias et al., 2007) randomized patients to receive gait training using the GT1 device or time-matched conventional rehabilitation. Muscle strength was measured using the MI at post-treatment (5 weeks) and follow-up (3 months). No significant between-group difference was found at either time point.

Conclusion: There is moderate evidence (level 1b) from one high quality RCT that end-effector gait trainers (+ sham stimulation) are more effective than a comparison intervention (conventional overground walking exercises) for improving lower extremity muscle strength in the chronic phase of stroke recovery.
Note: One fair quality RCT found that end-effector gait trainers are not more effective than conventional rehabilitation.
Note: The high quality RCT found that GT1+tDCS is more effective than conventional walking exercises. There is no significant difference between end-effector gait training with/without tDCS.

Two high quality RCTs (Peurala et al., 2005; Geroin et al., 2011) and one fair quality RCT (Dias et al., 2007) investigated the effect of end-effector gait trainers on spasticity in the chronic phase of stroke recovery.

The first high quality RCT (Peurala et al., 2005) randomized patients to receive (1) gait training using the GT1 device, (2) gait training + Functional Electrical Stimulation (GT1+FES), or (3) overground walking training. Lower extremity spasticity was measured by the Modified Ashworth Scale (MAS) at mid-treatment (2 weeks), post-treatment (3 weeks) and follow-up (6 months). No significant differences were found at any time point.

The second high quality RCT (Geroin et al., 2011) randomized patients to receive (1) gait training using the GT1 device + sham stimulation (GT1 + sham stimulation), (2) gait training + transcranial direct current stimulation (GT1+tDCS), or (3) conventional overground walking exercises. Spasticity was measured using the MAS (hip adductors, quadriceps femoris, ankle plantiflexors) at post-treatment (2 weeks) and follow-up (4 weeks). A significant between-group difference was found at both time points in favour of GT1 + sham stimulation vs. conventional walking exercises.
Note: A significant between-group difference was found at both time points in favour of GT1+tDCS vs. conventional walking exercises. No significant difference was found between GT1 + sham stimulation vs. GT1+tDCS.

The fair quality RCT (Dias et al., 2007) randomized patients to receive gait training using the GT1 device or time-matched conventional rehabilitation. Spasticity was measured using the MAS at post-treatment (5 weeks) and follow-up (3 months). No significant between-group difference was found at either time point.

Conclusion: There is conflicting evidence (Level 4) regarding the effect of end-effector gait trainers on spasticity in the chronic phase of stroke recovery. One high quality RCT found that end-effector gait trainers were more effective than conventional walking exercises, whereas a second high quality RCT and a fair quality RCT found that end-effector gait trainers were not more effective than comparison interventions (overground walking training, conventional rehabilitation).
Note: A high quality RCT found that GT1+tDCS was more effective than conventional overground walking training. There was no significant difference between end-effector gait training with/without tDCS.

Two high quality RCTs (Peurala et al., 2005; Geroin et al., 2011) and one fair quality RCT (Dias et al., 2007) investigated the effect of end-effector gait trainers on walking endurance in the chronic phase of stroke recovery.

The first high quality RCT Peurala et al., 2005) randomized patients to receive (1) gait training using the GT1 device, (2) gait training + Functional Electrical Stimulation (GT1+FES) group, or (3) overground walking training. Walking endurance was measured by the 6 Minute Walk Test (6MWT) at mid-treatment (2 weeks), post-treatment (3 weeks) and follow-up (6 months). No significant between-group differences were found at any time point.

The second high quality RCT (Geroin et al., 2011) randomized patients to receive (1) gait training using the GT1 device + sham stimulation (GT1 + sham stimulation), (2) gait training + transcranial direct current stimulation (GT1+tDCS), or (3) conventional overground walking exercises. Walking endurance was measured using the 6MWT at post-treatment (2 weeks) and follow-up (4 weeks). A significant between-group difference was found at both time points in favour of GT1 + sham stimulation vs. conventional walking exercises.
Note: A significant between-group difference was found at both time points in favour of GT1+tDCS vs. conventional walking exercises. No significant difference was found between GT1 + sham stimulation vs. GT1+tDCS at either time point.

The fair quality RCT (Dias et al., 2007) randomized patients to receive gait training using the GT1 device, or time-matched conventional rehabilitation. Walking endurance was measured using the 6MWT at post-treatment (5 weeks) and follow-up (3 months). No significant between-group difference was found at either time point.

Conclusion: There is conflicting evidence (Level 4) regarding the effect of end-effector gait trainers on walking endurance in the chronic phase of stroke recovery. One high quality RCT and one fair quality RCT found that end-effector gait trainers were not more effective than comparison interventions (overground walking training, conventional rehabilitation), whereas a second high quality RCT found that end-effector gait trainers were more effective than conventional walking exercises.
Note: One high quality RCT found that GT1+FES is not more effective than overground walking training, whereas a second high quality RCT found that GT1+tDCS is more effective than conventional overground walking exercises. There is no significant difference between end-effector gait training with/without FES, nor between end-effector gait training with/without tDCS.

Two high quality RCTs (Peurala et al., 2005; Geroin et al., 2011), two fair quality RCTs (Dias et al., 2007) and a fair non-randomized study (Park et al., 2015) investigated the effect of end-effector gait trainers on walking speed in the chronic phase of stroke recovery.

The first high quality RCT (Peurala et al., 2005) randomized patients to receive (1) gait training using the GT1 device, (2) gait training + Functional Electrical Stimulation (GT1+FES), or (3) overground walking training. Walking speed was measured using a 10-meter walking test at mid-treatment (2 weeks), post-treatment (3 weeks) and follow-up (6 months). No significant between-group differences were seen at any time point.

The second high quality RCT (Geroin et al., 2011) randomized patients to receive (1) gait training using the GT1 device + sham stimulation (GT1 + sham stimulation), (2) gait training + transcranial direct current stimulation (GT1+tDCS), or (3) conventional overground walking exercises. Walking speed was measured using a 10-meter walking test at post-treatment (2 weeks) and follow-up (4 weeks). A significant between-group difference was found at both time points in favour of GT1 + sham stimulation vs. conventional walking exercises.
Note: A significant between-group difference was found at both time points in favour of GT1+tDCS vs. conventional walking exercises. No significant difference was found between GT1 + sham stimulation vs. GT1+tDCS.

The fair quality RCT (Dias et al., 2007) randomized patients to receive gait training using the GT1 device or time-matched conventional rehabilitation. Walking speed was measured using a 10-meter walking test (Velocity, Step length, Step cadence with and without gait aid) at post-treatment (5 weeks) and follow-up (3 months). No significant between-group differences were found at either time point.

The fair non-randomized controlled trial (Park et al., 2015) assigned patients to receive gait training using the GT2 device or conventional overground gait training. Walking speed was measured using a 10-meter walking test at post-treatment (4 weeks). No significant between-group difference was found.

Conclusion: There is conflicting evidence (Level 4) regarding the effect of end-effector gait trainers on walking speed in the chronic phase of stroke recovery. One high quality RCT, one fair quality RCT and one fairnon-randomized study found that end-effector gait trainers were not more effective than comparison interventions (overground walking training, conventional rehabilitation, overground gait training), whereas a second high quality RCT found end-effector gait trainers were more effective than conventional overground walking exercises.
Note: One high quality RCT found that GT1+FES is not more effective than overground walking training; a second high quality RCT found that GT1+tDCS is more effective than conventional overground walking exercises. There is no significant difference between end-effector gait training with/without FES, nor between end-effector gait training with/without tDCS.

One high quality RCT (Kelley et al., 2013) and two fair quality RCTs (Hornby et al., 2008; Cho et al., 2015) investigated the effect of exoskeleton gait trainers on ADLs or IADLs in patients with chronic stroke.

The high quality RCT (Kelley et al., 2013) randomized patients to receive gait training using the Lokomat device or overground gait training. ADLs were measured by the Barthel Index (BI) at post-treatment (8 weeks) and follow-up (3 months). No significant between-group difference was found at either timepoint.

The first fair quality RCT (Hornby et al., 2008) randomized patients to receive locomotor training using the Lokomat device or therapist-assisted locomotor treadmill training. IADLs were measured using the Frenchay Activities Index at post-treatment (12 sessions) and follow-up (6 months). No significant between-group difference was found at either timepoint.

The second fair quality (crossover) RCT (Cho et al., 2015) randomized patients to receive gait training using the Lokomat device or no additional gait training; both groups received conventional physical therapy. ADLs were measured using the modified BI (mBI – Total, Transfers, Ambulation scores) at post-treatment (4 weeks, 8 weeks). A significant between-group difference was found in one measure (mBI – Transfers), in favour of exoskeleton gait training vs. no gait training.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and two fair quality RCTs that exoskeleton gait trainers are not more effective than no gait training or comparison interventions (overground gait training, treadmill training, no gait training) for improving ADLs/IADLs in the chronic phase of stroke recovery.

One fair quality RCT (dos Santos et al., 2018) investigated the effect of an exoskeleton gait trainer on ataxia in the chronic phase of stroke recovery. The fair quality RCT randomized patients with chronic stroke and ataxia to receive gait training using the Lokomat 5.0 or therapist-assisted gait training. Ataxia was measured using the Scale for the Assessment and Rating of Ataxia at post-treatment (5 months). No significant between-group difference was found.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that exoskeleton gait trainers are not more effective than a comparison intervention (therapist-assisted gait training) for improving ataxia in the chronic phase of stroke recovery.

Two high quality RCTs (Westlake & Patten, 2009; Bang & Shin, 2016) and three fair quality RCTs (Hornby et al., 2008; Cho et al., 2015; dos Santos et al., 2018) investigated the effect of exoskeleton gait trainers on balance in the chronic phase or stroke recovery.

The first high quality RCT (Westlake & Patten, 2009) randomized patients to receive gait training using the Lokomat device or time-matched manually-assisted body-weight supported treadmill training. Balance was measured by the Berg Balance Scale (BBS) at post-treatment (4 weeks). No significant between-group difference was found.

The second high quality RCT (Bang & Shin, 2016) randomized patients to receive gait training using the Lokomat device or treadmill gait training. Balance was measured using the BBS at post-treatment (4 weeks). A significant between-group difference was found, in favour of exoskeleton gait training vs. treadmill gait training.

The first fair quality RCT (Hornby et al., 2008) randomized patients to receive locomotor training using the Lokomat device or therapist-assisted locomotor treadmill training. Balance was measured using the BBS at post-treatment (12 sessions) and follow-up (6 months). No significant between-group difference was found at either timepoint.

The second fair quality (crossover) RCT (Cho et al., 2015) randomized patients to receive gait training using the Lokomat device or no additional gait training; both groups received conventional physical therapy. Balance was measured using the BBS and the modified Functional Reach Test (Forward, Lateral) at post-treatment (4 weeks, 8 weeks). No significant between-group differences were found on either measure.

The third fair quality RCT (dos Santos et al., 2018) randomized patients with chronic stroke and ataxia to receive gait training using the Lokomat 5.0 or therapist-assisted gait training. Balance was measured using the BBS at post-treatment (5 months). No significant between-group difference was found.

Conclusion: There is conflicting evidence (Level 4) regarding the effect of exoskeleton gait trainers on balance in the chronic phase of stroke recovery. One high quality RCT and three fair quality RCTs found that the Lokomat device was not more effective than comparison interventions (manually-assisted body-weight supported treadmill training, therapist-assisted locomotor treadmill training, no gait training, therapist-assisted gait training), whereas one high quality RCT found that the Lokomat device was more effective than treadmill gait training.

One high quality RCT (Bang & Shin, 2016) investigated the effect of an exoskeleton gait trainer on balance confidence in the chronic phase or stroke recovery. This high quality RCT randomized patients to receive gait training using the Lokomat device or treadmill gait training. Balance confidence was measured using the Activities-Specific Balance Confidence scale at post-treatment (4 weeks). Significant between-group difference was found, in favour of exoskeleton gait training vs. treadmill gait training.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that exoskeleton gait trainers are more effective than a comparison intervention (treadmill gait training) for improving balance confidence in the chronic phase of stroke recovery.

Two fair quality RCTs (Hornby et al., 2008; Cho et al., 2015) investigated the effect of exoskeleton gait trainers on functional ambulation in the chronic phase of stroke recovery.

The first fair quality RCT (Hornby et al., 2008) randomized patients to receive locomotor training using the Lokomat device or therapist-assisted locomotor treadmill training. Functional ambulation was measured using the modified Emory Functional Ambulation Profile at post-treatment (12 sessions) and follow-up (6 months). No significant between-group difference was found at either timepoint.

The second fair quality (crossover) RCT (Cho et al., 2015) randomized patients to receive gait training using the Lokomat device or no additional gait training; both groups received conventional physical therapy. Functional ambulation was measured using the Functional Ambulation Category at post-treatment (4 weeks, 8 weeks). No significant between-group difference was found.

Conclusion: There is limited evidence (Level 2a) from two fair quality RCTs that exoskeleton gait trainers are not more effective than no gait training or a comparison intervention (therapist-assisted treadmill training) for improving functional ambulation in the chronic phase of stroke recovery.

One high quality RCT (Kelley et al., 2013) and one fair quality RCT (dos Santos et al., 2018) investigated the effect of exoskeleton gait trainers on functional independence in the chronic phase of stroke recovery.

The high quality RCT (Kelley et al., 2013) randomized patients to receive gait training using the Lokomat device or overground gait training. Functional independence was measured by the Functional Independence Measure (FIM – Locomotion subtest) at post-treatment (8 weeks) and follow-up (3 months). No significant between-group difference was found at either timepoint.

The fair quality RCT (dos Santos et al., 2018) randomized patients with chronic stroke and ataxia to receive gait training using the Lokomat 5.0 or therapist-assisted gait training. Functional independence was measured using the FIM at post-treatment (5 months). No significant between-group difference was found.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and one fair quality RCT that exoskeleton gait trainers are not more effective than comparison interventions (overground gait training, therapist-assisted gait training) for improving functional independence in the chronic phase of stroke recovery.

Two high quality RCTs (Westlake & Patten 2009,; Bang & Shin, 2016) and one fair quality RCT (Hornby et al., 2008) investigated the effect of exoskeleton gait trainers on gait parameters in the chronic phase of stroke recovery.

The first high quality RCT (Westlake & Patten, 2009) randomized patients to receive gait training using the Lokomat device or time-matched manually-assisted body-weight supported treadmill training. Gait parameters were measured using the GAITRite system (Self-selected walking speed, Fast walking speed, Step length ratio of paretic limb) at post-treatment (4 weeks). No significant between-group differences were found.

The second high quality RCT (Bang & Shin, 2016) randomized patients to receive gait training using the Lokomat device or treadmill gait training. Gait parameters was measured using the GAITRite system (Gait speed, Cadence, Step length, Double limb support period) at post-treatment (4 weeks). Significant between-group differences were found on all measures, in favour of exoskeleton gait training vs. treadmill gait training.

The fair quality RCT (Hornby et al., 2008) randomized patients to receive gait training using the Lokomat device or therapist-assisted locomotor treadmill training. Gait parameters (% Single limb stance, Step asymmetry: self-selected velocity/fast velocity) were measured at post-treatment (12 sessions) and follow-up (6 months). A significant between-group difference in one measure (% Single limb stance – Fast velocity) was found at post-treatment, in favour of therapist-assisted locomotor treadmill training vs. exoskeleton gait training. Results did not remain significant at follow-up.

Conclusion: There is conflicting evidence (Level 4) regarding the effect of exoskeleton gait trainers on gait parameters in the chronic phase of stroke recovery. One high quality RCT and one fair quality RCT found that the Lokomat gait trainer was not more effective than comparison interventions (body-weight supported treadmill training, therapist-assisted treadmill training), whereas a second high quality RCT found that the Lokomat gait trainer was more effective than treadmill training.

One high quality RCT (Lewek et al., 2009) investigated the effect of an exoskeleton gait trainer on lower extremity kinematics in the chronic phase of stroke recovery. The high quality RCT randomized patients to receive gait training using the Lokomat device or therapist-assisted treadmill training. Kinematic coordination was measured according to the consistency of intralimb hip and knee angular trajectories over gait cycles (average coefficient of correspondence (ACC): Hip – involved/uninvolved; Knee – involved/uninvolved) at post-treatment (4 weeks). No between-group differences were found.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that an exoskeleton gait trainer is not more effective than a comparison intervention (treadmill training) for improving lower extremity kinematics in the chronic phase of stroke recovery.

Two fair quality RCTs (Ukar, Paker, & Bugdayci, 2014; dos Santos et al., 2018) investigated the effect of exoskeleton gait trainers on mobility in the chronic phase of stroke recovery.

The first fair quality RCT (Ukar, Paker, & Bugdayci, 2014) randomized patients to receive gait training using the Lokomat device or time-matched conventional physical therapy home exercises. Mobility was measured using the Timed Up and Go test (TUG) at post-treatment (2 weeks) and follow-up (8 weeks). A significant between-group difference was found at both time points, in favour of exoskeleton gait training vs. conventional home exercises.

The second fair quality RCT (dos Santos et al., 2018) randomized patients with chronic stroke and ataxia to receive gait training using the Lokomat 5.0 or therapist-assisted gait training. Mobility was measured using the TUG at post-treatment (5 months). No significant between-group difference was found.

Conclusion: There is conflicting evidence (Level 4) regarding the effect of exoskeleton gait trainers on mobility in the chronic phase of stroke recovery. One fair quality RCT found that the Lokomat gait trainer was more effective than home exercises, whereas a second fair quality RCT found that the Lokomat device was not more effective than therapist-assisted gait training.

Two high quality RCTs (Westlake & Patten, 2009; Kelley et al., 2013) and one fair quality RCT (Cho et al., 2015) investigated the effect of exoskeleton gait trainers on lower extremity motor function in the chronic phase of stroke recovery.

The first high quality RCT (Westlake & Patten, 2009) randomized patients to receive gait training using the Lokomat device or time-matched manually-assisted body-weight supported treadmill training. Lower extremity motor function was measured using the Fugl-Meyer Assessment – Lower Extremity (FMA-LE) and the short physical performance battery at post-treatment (4 weeks). No significant between-group differences were found.

The second high quality RCT (Kelley et al., 2013) randomized patients to receive gait training using the Lokomat device or overground gait training. Lower extremity motor function was measured by the FMA-LE at post-treatment (8 weeks) and follow-up (3 months). No significant between-group difference was found at either timepoint.

The fair quality (crossover) RCT (Cho et al., 2015) randomized patients to receive gait training using the Lokomat device or no additional gait training; both groups received conventional physical therapy. Lower extremity motor function was measured using the FMA-LE at post-treatment (4 weeks, 8 weeks). No significant between-group difference was found.

Conclusion: There is strong evidence (Level 1a) from two high quality RCTs and one fair quality RCT that exoskeleton gait trainers are not more effective than comparison interventions (body-weight supported treadmill training, overground gait training, no additional gait training) for improving lower extremity motor function in the chronic phase of stroke recovery.

One fair quality RCT (Cho et al., 2015) investigated the effect of an exoskeleton gait trainer on lower extremity muscle strength in the chronic phase of stroke recovery. This fair quality (crossover) RCT randomized patients to receive gait training using the Lokomat device or no additional gait training; both groups received conventional physical therapy. Lower extremity muscle strength was measured using the Motricity Index at post-treatment (4 weeks, 8 weeks). No significant between-group difference was found.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that exoskeleton gait trainers are not more effective than no additional training for improving lower extremity strength in the chronic phase of stroke recovery.

One high quality RCT (Westlake & Patten, 2009) investigated the effect of an exoskeleton gait trainer on participation in life events in the chronic phase of stroke recovery. This high quality RCT randomized patients to receive gait training using the Lokomat device or time-matched manually-assisted body-weight supported treadmill training. Participation in life events was measured using the Late Life Function and Disability Instrument (LLFDI: Disability Frequency, Disability Limitation, Function) at post-treatment (4 weeks). No significant between-group differences were found.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that an exoskeleton gait trainer is not more effective than a comparison intervention (body-weight supported treadmill training) for improving participation in life events in the chronic phase of stroke recovery.

One fair quality RCT (Hornby et al., 2008) investigated the effect of an exoskeleton gait trainer on quality of life in the chronic phase of stroke recovery. This fair quality RCT randomized patients to receive gait training using the Lokomat device or therapist-assisted locomotor treadmill training. Quality of life was measured using the Medical Outcomes Questionnaire Short Form – 36 (SF-36 – Physical component summary score) at post-treatment (12 sessions) and follow-up (6 months). A significant between-group difference was found at post-treatment in a subgroup of participants with severe gait deficits (walking velocity ≤ 0.5m/s), in favour of therapist-assisted locomotor treadmill training vs. exoskeleton gait training. Results did not remain significant at follow-up.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that exoskeleton gait trainers are not more effective than a comparison intervention (therapist-assisted treadmill training) for improving quality of life in the chronic phase of stroke recovery.
Note: In fact, the fair quality RCT found that therapist-assisted treadmill training was more effective than the Lokomat gait trainer.

One fair quality RCT (Cho et al., 2015) investigated the effect of an exoskeleton gait trainer on muscle tone in the chronic phase of stroke recovery. The fair quality (crossover) RCT randomized patients to receive gait training using the Lokomat device or no additional gait training; both groups received conventional physical therapy. Spasticity was measured using the Modified Ashworth Scale at post-treatment (4 weeks, 8 weeks). No significant between-group difference was found.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that an exoskeleton gait trainer is not more effective no additional gait training for reducing spasticity in the chronic phase of stroke recovery.

One high quality RCT (Kelley et al., 2013) investigated the effect of an exoskeleton gait trainer on stroke outcomes in the chronic phase of stroke recovery. This high quality RCT randomized patients to receive gait training using the Lokomat device or overground gait training. Stroke impact was measured by the Stroke Impact Scale (SIS – Strength, Mobility, ADL/IADL, Social participation, Total recovery scores) at post-treatment (8 weeks) and follow-up (3 months). No significant between-group differences were found at either timepoint.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that exoskeleton gait trainers are not more effective than a comparison intervention (overground gait training) for reducing the impact of stroke in the chronic phase of stroke recovery.

Two high quality RCTs (Westlake & Patten, 2009; Kelley et al., 2013) and one fair quality RCT (Hornby et al., 2008) investigated the effect of exoskeleton gait trainers on walking endurance in the chronic phase of stroke recovery.

The first high quality RCT (Westlake & Patten, 2009) randomized patients to receive gait training using the Lokomat device or time-matched manually-assisted body-weight supported treadmill training. Walking endurance was measured by the 6 Minute Walk Test (6MWT) at post-treatment (4 weeks). No significant between-group difference was found.

The second high quality RCT (Kelley et al., 2013) randomized patients to receive gait training using the Lokomat device or overground gait training. Walking endurance was measured by the 6MWT at post-treatment (8 weeks) and follow-up (3 months). No significant between-group difference was found at either timepoint.

The fair quality RCT (Hornby et al., 2008) randomized patients to receive gait training using the Lokomat device or therapist-assisted treadmill training. Walking endurance was measured using the 6MWT at post-treatment (12 sessions) and follow-up (6 months). No significant between-group difference was found at either timepoint.

Conclusion: There is strong evidence (Level 1a) from two high quality RCTs and one fair quality RCT that exoskeleton gait trainers are not more effective than comparison interventions (body-weight supported treadmill training, overground gait training, treadmill training) for improving walking endurance in the chronic phase of stroke recovery.

One high quality RCT (Kelley et al., 2013) and two fair quality RCTs (Hornby et al., 2008; Ukar, Paker, & Bugdayci, 2014) investigated the effect of exoskeleton gait trainers on walking speed in the chronic phase of stroke recovery.

The high quality RCT (Kelley et al., 2013) randomized patients to receive gait training using the Lokomat device or overground gait training. Walking speed was measured by the 10-meter walking test at post-treatment (8 weeks) and follow-up (3 months). No significant between-group difference was found at either timepoint.

The first fair quality RCT (Hornby et al., 2008) randomized patients to receive gait training using the Lokomat device, or therapist-assisted treadmill training. Walking speed was measured by the 10-meter walking test using the GaitMat device (Self-selected velocity, Fast velocity) at post-treatment (12 sessions) and follow-up (6 months). Significant between-group differences on all measures were found at post-treatment, in favour of therapist-assisted treadmill training vs. exoskeleton gait training. Results did not remain significant at follow-up.

The second fair quality RCT (Ukar, Paker, & Bugdayci, 2014) randomized patients to receive gait training using the Lokomat device or time-matched conventional physical therapy home exercises. Walking speed was measured using the 10-meter walking test at post-treatment (2 weeks) and follow-up (8 weeks). A significant between-group difference was found at both time points, in favour of exoskeleton gait training vs. home exercises.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and one fair quality RCT that exoskeleton gait trainers are not more effective than comparison interventions (overground gait training, treadmill training) for improving walking speed in the chronic phase of stroke recovery. In fact, the fair quality RCT found that therapist-assisted treadmill training was more effective than gait training using the Lokomat device.
Note: However, a second fair quality RCT found that gait training with the Lokomat device was more effective than home exercises.

Four high quality RCTs (Tong et al., 2006; Ng et al., 2008; Morone et al., 2011; Chua, Culpan & Menon, 2016) examined the effect of end-effector gait trainers on activities of daily living (ADLs) following stroke.

The first high quality RCT (Tong et al., 2006) randomized patients with acute/subacute stroke to receive (1) gait training using the GT1 device, (2) gait training and Functional Electrical Stimulation (GT1+FES), or (3) conventional overground gait training. ADLs were measured using the Barthel Index (BI) at post-treatment (4 weeks). No significant between-group differences were found.

The second high quality RCT (Ng et al., 2008) randomized patients with acute/subacute stroke to receive (1) gait training using the GT2 device, (2) gait training + Functional Electrical Stimulation (GT2+FES), or (3) conventional gait training. ADLs were measured using the BI at post-treatment (4 weeks) and follow-up (6 months). No significant between-group differences were found at either timepoint.

The third high quality RCT (Morone et al., 2011) randomized patients with acute/subacute stroke to receive gait training using the GT1 device or conventional gait training. Patients were stratified by level of motor impairment (Motricity Index score ≤29: low motricity, > 29: high motricity). ADLs were measured using the BI at post-treatment (4 weeks) and at discharge (average 86-102 days post-stroke according to level of impairment); discharge results were reported. A significant difference was found between low motricity groups only, in favour of end-effector gait training vs. conventional gait training.

The fourth high quality RCT (Chua, Culpan & Menon, 2016) randomized patients with acute/subacute stroke to receive gait training using the GT1 device or time-matched conventional physical therapy. ADLs was measured by the BI at mid-treatment (4 weeks), post-treatment (8 weeks) and follow-up (12 weeks, 24 weeks, 48 weeks). No significant between-group difference was found at any time point.

Conclusion: There is strong evidence (Level 1a) from four high quality RCTs that end-effector gait trainers are not more effective than comparison interventions (conventional overground gait training, physical therapy) for improving ADLs following stroke.
Note: One high quality RCT found that end-effector gait training is more effective than conventional gait training for improving ADLs in patients with low motricity (MI score ≤29).
Note: Two high quality RCTs found that end-effector gait training + Functional Electrical Stimulation is not more effective than conventional overground gait training. There is no significant difference between end-effector gait training with/without FES.

Four high quality RCTs (Tong et al., 2006; Ng et al., 2008; Freivogel, Schmalohr & Mehrholz, 2009; Morone et al., 2011) investigated the effect of end-effector gait trainers on balance following stroke.

The first high quality RCT (Tong et al., 2006) randomized patients with acute/subacute stroke to receive (1) gait training using the GT1 device, (2) gait training and Functional Electrical Stimulation (GT1+FES), or (3) conventional overground gait training. Balance was measured using the Berg Balance Scale (BBS) at mid-treatment (2 weeks) and post-treatment (4 weeks). No significant between-group differences were found at either time point.

The second high quality RCT (Ng et al., 2008) randomized patients with acute/subacute stroke to receive (1) gait training using the GT2 device, (2) gait training + Functional Electrical Stimulation (GT2+FES), or (3) conventional gait training. Balance was measured by the BBS at post-treatment (4 weeks) and follow-up (6 months). No significant between-group differences were found at either timepoint.

The third high quality cross-over RCT (Freivogel, Schmalohr & Mehrholz, 2009) randomized patients with subacute/chronic stroke to receive gait training using the LokoHelp electromechanical device or conventional treadmill/overground gait training. Balance was measured using the BBS at post-treatment (6 weeks). No significant between-group difference was found.

The fourth high quality RCT (Morone et al., 2011) randomized patients with acute/subacute stroke to receive gait training using the GT1 device or conventional gait training. Patients were stratified by level of motor impairment (Motricity Index score ≤29: low motricity, > 29: high motricity). Balance was measured using the Trunk Control Test at post-treatment (4 weeks) and at discharge (average 86-102 days post-stroke according to level of impairment); discharge results were reported. A significant difference was found between low motricity groups only, in favour of end-effector gait training vs. conventional gait training.

Conclusion: There is strong evidence (Level 1a) from four high quality RCTs that end-effector gait trainers are not more effective than comparison interventions (conventional overground gait training, conventional treadmill training) following stroke.
Note: One high quality RCT found that end-effector gait training is more effective than conventional gait training for improving balance in patients with low motricity (MI score ≤ 29).
Note: Two high quality RCTs found that end-effector gait training with Functional Electrical Stimulation (FES) is not more effective than conventional overground gait training. There is no difference between end-effector gait training with/without FES.

One high quality RCT (Morone et al., 2011) investigated the effect of an end-effector gait trainer on disability following stroke. The high quality RCT randomized patients with acute/subacute stroke to receive gait training using the GT1 device or conventional gait training. Patients were stratified by level of motor impairment (Motricity Index score ≤ 29: low motricity, > 29: high motricity). Disability was measured using the Rankin Scale at post-treatment (4 weeks) and at discharge (average 86-102 days post-stroke according to level of impairment); discharge results were reported. A significant difference was found between low motricity groups only, in favour of end-effector gait training vs. conventional gait training.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that end-effector gait training is more effective than a comparison intervention (conventional gait training) for reducing disability among patients with low motricity following stroke.
Note: End-effector gait training is not more effective than conventional gait training for improving disability among patients with high motricity.

Five high quality RCTs (Tong et al., 2006; Ng et al., 2008; Freivogel, Schmalohr & Mehrholz, 2009; Morone et al., 2011; Chua, Culpan & Menon, 2016) and one non-randomized study (Hesse et al., 2001) investigated the effect of end-effector gait trainers on functional ambulation following stroke.

The first high quality RCT (Tong et al., 2006) randomized patients with acute/subacute stroke to receive (1) gait Training using the GT1 device, (2) gait training and Functional Electrical Stimulation (GT1+FES), or (3) conventional overground gait training. Functional ambulation was measured using the Functional Ambulation Categories (FAC) at mid-treatment (2 weeks) and post-treatment (4 weeks). Significant between-group differences were found at both time points, in favour of end-effector gait training vs. conventional overground gait training.
Note: Significant between-group differences in functional ambulation were found at both time points, in favour of GT1+FES vs. conventional overground gait training. There were no significant differences between end-effector gait training vs. GT1+FES.

The second high quality RCT (Ng et al., 2008) randomized patients with acute/subacute stroke to receive (1) gait training using the GT2 device, (2) gait training + Functional Electrical Stimulation (GT2+FES), or (3) conventional gait training. Functional ambulation was measured by the FAC at post-treatment (4 weeks) and follow-up (6 months). A significant difference was found at follow-up only, in favour of end-effector gait training vs. conventional gait training.
Note: A significant difference was found at both timepoints, in favour of GT2+FES vs. conventional gait training. No significant difference was found between end-effector gait training vs. GT2+FES at either timepoint.

The third high quality cross-over RCT (Freivogel, Schmalohr & Mehrholz, 2009) randomized patients with subacute/chronic stroke to receive gait training using the LokoHelp electromechanical device or conventional treadmill/overground gait training. Functional ambulation was measured using the FAC at post-treatment (6 weeks). No significant between-group difference was found.

The fourth high quality RCT (Morone et al., 2011) randomized patients with acute/subacute stroke to receive gait training using the GT1 device or conventional gait training. Patients were stratified by level of motor impairment (Motricity Index score ≤ 29: low motricity, > 29: high motricity). Functional ambulation was measured using the FAC at post-treatment (4 weeks) and at discharge (average 86-102 days post-stroke according to level of impairment); discharge results were reported. A significant difference was found between low motricity groups only, in favour of end-effector gait training vs. conventional gait training.

The fifth high quality RCT (Chua, Culpan & Menon, 2016) randomized patients with acute/subacute stroke to receive gait training using the GT1 device or time-matched conventional physical therapy. Functional ambulation was measured using the FAC at mid-treatment (4 weeks), at post-treatment (8 weeks), and follow-up (12 weeks, 24 weeks, 48 weeks). No significant between-group difference was found at any time point.

The non-randomized controlled trial (Hesse et al., 2001) assigned patients with subacute/chronic stroke who were wheelchair-dependent to receive gait training using the GT1 device in addition to conventional physical therapy. Functional ambulation was measured using the FAC at post-treatment (4 weeks). No significant improvement was seen.

Conclusion: There is conflicting evidence (Level 4) regarding the effect of end-effector gait trainers on functional ambulation following stroke. One high quality RCT found that end-effector gait trainers are more effective than conventional overground gait training at mid-treatment and post-treatment; another high quality RCT found that end-effector gait trainers are more effective than conventional gait training in the long term; and a third high quality RCT found that end-effector gait trainers are more effective than conventional gait training in patients with low motricity but not those with high motricity. However, two high quality RCTs and one non-randomized study found that end-effector gait trainers are not more effective than comparison interventions (conventional treadmill/overground gait training, conventional physical therapy).
Note: Two high quality RCTs found that end-effector gait training + Functional Electrical Stimulation (FES) is more effective than overground gait training. There is no difference between end-effector gait training with/without FES.

Two high quality RCTs (Tong et al., 2006; Ng et al., 2008) investigated the effect of end-effector gait trainers on functional independence following stroke.

The first high quality RCT (Tong et al., 2006) randomized patients with acute/subacute stroke to receive (1) gait training using the GT1 device, (2) gait training and Functional Electrical Stimulation (GT1+FES), or (3) conventional overground gait training. Functional independence was measured using the Functional Independence Measure (FIM) at post-treatment (4 weeks). No significant between-group differences were found.

The second high quality RCT (Ng et al., 2008) randomized patients with acute/subacute stroke to receive (1) gait training using the GT2 device, (2) gait training + Functional Electrical Stimulation (GT2+FES), or (3) conventional gait training. Functional independence was measured by the Functional Independence Measure (FIM) at post-treatment (4 weeks) and follow-up (6 months). No significant differences were found at either timepoint.

Conclusion: There is strong evidence (Level 1a) from two high quality RCTs that end-effector gait trainers are not more effective than comparison interventions (conventional overground gait training) for improving functional independence following stroke.
Note: Two high quality RCTs found that end-effector gait training with Functional Electrical Stimulation (FES) is not more effective than conventional overground gait training. There is no difference between end-effector gait training with/without FES.

One non-randomized study (Hesse et al., 2001) investigated the effect of end-effector gait trainers on gait parameters following stroke. The non-randomized controlled trial assigned patients with subacute/chronic stroke who were wheelchair-dependent to receive gait training using the GT1 device in addition to conventional physical therapy. Gait parameters (velocity, cadence, stride length) and limb-dependent cycle parameters (single-stance period, double-stance phase, stance duration, swing duration, swing symmetry, stance symmetry) were measured at post-treatment (4 weeks). Significant improvements were seen (velocity, cadence, stride length, single-stance period, terminal double-stance phase, swing symmetry).

Conclusion: There is limited evidence (Level 2b) from one non-randomized study that end-effector gait trainers are effective for improving gait parameters following stroke.

Four high quality RCTs (Tong et al., 2006; Ng et al., 2008; Freivogel, Schmalohr & Mehrholz, 2009; Morone et al., 2011) and one non-randomized study (Hesse et al., 2001) investigated the effect of end-effector gait trainers on mobility following stroke.

The first high quality RCT (Tong et al., 2006) randomized patients with acute/subacute stroke to receive (1) gait training using the GT1 device, (2) gait training and Functional Electrical Stimulation (GT1+FES), or (3) conventional overground gait training. Mobility was measured using the Elderly Mobility Scale at mid-treatment (2 weeks) and post-treatment (4 weeks). A significant between-group difference was found at post-treatment, in favour of end-effector gait training vs. conventional overground gait training.
Note: A significant between-group differences was found at post-treatment in favour of GT1+FES vs. conventional overground gait training. No significant difference between end-effector gait training vs. GT1+FES was found at either timepoint.

The second high quality RCT (Ng et al., 2008) randomized patients with acute/subacute stroke to receive (1) gait training using the GT2 device, (2) gait training + Functional Electrical Stimulation (GT2+FES), or (3) conventional gait training. Mobility was measured by the Elderly Mobility Scale at post-treatment (4 weeks) and follow-up (6 months). Significant between-group differences were found at both timepoints, in favour of end-effector gait training vs. conventional gait training.
Note: Significant between-group differences were found at both timepoints, in favour of GT2+FES vs. conventional gait training. No significant difference was found between end-effector gait training vs. GT2+FES at either timepoint.

The third high quality cross-over RCT (Freivogel, Schmalohr & Mehrholz, 2009) randomized patients with subacute/chronic stroke to receive gait training using the LokoHelp electromechanical device or conventional treadmill/overground gait training. Mobility was measured using the Rivermead Mobility Index (RMI) at post-treatment (6 weeks). No significant between-group difference was found.

The fourth high quality RCT (Morone et al., 2011) randomized patients with acute/subacute stroke to receive gait training using the GT1 device or conventional gait training. Patients were stratified by level of motor impairment (Motricity Index score ≤29: low motricity, > 29: high motricity). Mobility was measured using the RMI at post-treatment (4 weeks) and at discharge (average 86-102 days post-stroke according to level of impairment); discharge results were reported. A significant difference was found between low motricity groups only, in favour of end-effector gait training vs. conventional gait training.

The The non-randomized controlled trial (Hesse et al., 2001) assigned patients with subacute/chronic stroke who were wheelchair-dependent to receive gait training using the GT1 device in addition to conventional physical therapy. Functional mobility was measured using the Rivermead Motor Assessment (Gross function, Legs and trunk scores) at post-treatment (4 weeks). No significant improvement was seen.

Conclusion: There is conflicting evidence (Level 4) regarding the effect of end-effector gait trainers on mobility following stroke. Two high quality RCTs found that end-effector gait trainers are more effective than conventional overground gait training, whereas another high quality RCT found that end-effector gait trainers are not more effective than conventional treadmill/overground gait training; these studies used different devices and outcome measures. A fourth high quality RCT found that an end-effector gait trainer was more effective than conventional gait training among patients with low motricity but not those with high motricity.
Note: Two high quality RCTs found that end-effector gait training with Functional Electrical Stimulation (FES) is more effective than conventional overground gait training. There is no difference between end-effector gait training with/without FES.

Four high quality RCTs (Tong et al., 2006; Ng et al., 2008; Freivogel, Schmalohr & Mehrholz, 2009; Morone et al., 2011) investigated the effect of end-effector gait trainers on lower extremity muscle strength following stroke.

Four high quality RCTs (Tong et al., 2006; Ng et al., 2008; Freivogel, Schmalohr & Mehrholz, 2009; Morone et al., 2011) investigated the effect of end-effector gait trainers on lower extremity muscle strength following stroke.

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Note: A significant between-group difference was found at post-treatment in favour of GT1+FES vs. conventional overground gait training. There was no significant difference between end-effector gait training vs. GT1+FES.

The second high quality RCT (Ng et al., 2008) randomized patients with acute/subacute stroke to receive (1) gait training using the GT2 device, (2) gait training + Functional Electrical Stimulation (GT2+FES), or (3) conventional gait training. Muscle strength was measured by the MI (Leg score) at post-treatment (4 weeks) and follow-up (6 months). No significant between-group differences were found at either timepoint.

The third high quality cross-over RCT (Freivogel, Schmalohr & Mehrholz, 2009) randomized patients with subacute/chronic stroke to receive gait training using the LokoHelp electromechanical device or conventional treadmill/overground gait training. Muscle strength was measured using the MI (Leg score) at post-treatment (6 weeks). No significant between-group difference was found.

The fourth high quality RCT (Morone et al., 2011) randomized patients with acute/subacute stroke to receive gait training using the GT1 device or conventional gait training. Patients were stratified by level of motor impairment (MI score ≤29: low motricity, > 29: high motricity). Muscle strength was measured using the Motricity Index at post-treatment (4 weeks) and at discharge (average 86-102 days post-stroke according to level of impairment); discharge results were reported. No significant between-group differences were found at either timepoint.

Conclusion: There is strong evidence (Level 1a) from three high quality RCTs that end-effector gait trainers are not more effective than comparison interventions (conventional overground/treadmill gait training) for improving lower extremity muscle strength following stroke.
Note: However, one high quality RCT found that end-effector gait training is more effective than conventional overground gait training.
Note: One high quality RCT found that end-effector gait training with Functional Electrical Stimulation (FES) is more effective than conventional overground gait training. Two high quality RCTs found no significant difference between end-effector gait training with/without FES.

One high quality RCT (Morone et al., 2011) investigated the effect of end-effector gait training on neurological status following stroke. The high quality RCT randomized patients with acute/subacute stroke to receive gait training using the GT1 device or conventional gait training. Patients were stratified by level of motor impairment (Motricity Index score ≤29: low motricity, > 29: high motricity). Neurological status was measured using the Canadian Neurological Scale at post-treatment (4 weeks) and at discharge (average 86-102 days post-stroke according to level of impairment); discharge results were reported. No significant between-group differences were found at either time point.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that end-effector gait trainers are not more effective than a comparison intervention (conventional gait training) for improving neurological status following stroke.

Two high quality RCTs (Freivogel, Schmalohr & Mehrholz, 2009; Morone et al., 2011) and one non-randomized study (Hesse et al., 2001) investigated the effect of end-effector gait training on spasticity following stroke.

The first high quality cross-over RCT (Freivogel, Schmalohr & Mehrholz, 2009) randomized patients with subacute/chronic stroke to receive gait training using the LokoHelp electromechanical device or conventional treadmill/overground gait training. Spasticity was measured using the Modified Ashworth Scale at post-treatment (6 weeks). No significant between-group difference was found.

The second high quality RCT (Morone et al., 2011) randomized patients with acute/subacute stroke to receive gait training using the GT1 device or conventional gait training. Patients were stratified by level of motor impairment (Motricity Index score ≤ 29: low motricity, > 29: high motricity). Spasticity was measured using the Ashworth Scale at post-treatment (4 weeks) and at discharge (average 86-102 days post-stroke according to level of impairment); discharge results were reported. No significant between-group differences were found at either time point.

The non-randomized controlled trial (Hesse et al., 2001) assigned patients with subacute/chronic stroke who were wheelchair-dependent to receive gait training using the GT1 device in addition to conventional physical therapy. Spasticity was measured using the Modified Ashworth Scale at post-treatment (4 weeks). No significant improvement was seen.

Conclusion: There is strong evidence (Level 1a) from two high quality RCTs that end-effector gait trainers are not more effective than comparison interventions (conventional overground/treadmill gait training,conventional gait training) for reducing spasticity following stroke. A non-randomized study also reported no significant improvement in spasticity following end-effector gait training.

One high quality RCT (Chua, Culpan & Menon, 2016) investigated the effect of end-effector gait training on stroke. The high quality RCT randomized patients with acute/subacute stroke to receive gait training using the GT1 device or time-matched conventional physical therapy. Stroke impact was measured by the Stroke Impact Scale (SIS – Physical, Memory and thinking, Mood and emotion, Communication, Participation, Recovery domains) at mid-treatment (4 weeks), post-treatment (8 weeks) and follow-up (12 weeks, 24 weeks, 48 weeks). No significant between-group difference was found at any time point.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that end-effector gait trainers are not more effective than a comparison intervention (conventional physical therapy) for reducing the impact of stroke.

Two high quality RCTs (Morone et al., 2011; Chua, Culpan & Menon, 2016) investigated the effect of end-effector gait training on walking endurance following stroke.

The first high quality RCT (Morone et al., 2011) randomized patients with acute/subacute stroke to receive gait training using the GT1 device or conventional gait training. Patients were stratified by level of motor impairment (Motricity Index score ≤29: low motricity, > 29: high motricity). Walking endurance was measured using the 6 Minute Walk Test (6MWT) at post-treatment (4 weeks) and at discharge (average 86-102 days post-stroke according to level of impairment); discharge results were reported. A significant difference was found between low motricity groups only, in favour of end-effector gait training vs. conventional gait training.

The second high quality RCT (Chua, Culpan & Menon, 2016) randomized patients with acute/subacute stroke to receive gait training using the GT1 device or time-matched conventional physical therapy. Walking endurance was measured by the 6MWT at mid-treatment (4 weeks), post-treatment (8 weeks) and follow-up (12 weeks, 24 weeks, 48 weeks). No significant between-group difference was found at any time point.

Conclusion: There is strong evidence (Level 1a) from two high quality RCTs that end-effector gait trainers are not more effective than comparison interventions (conventional gait training, conventional physical therapy) in improving walking endurance following stroke.
Note: However, one of these studies found that end-effector gait trainers are more effective than conventional gait training among patients with low motricity (but not those with high motricity).

Five high quality RCTs (Tong et al., 2006; Ng et al., 2008; Freivogel, Schmalohr & Mehrholz, 2009; Morone et al., 2011; Chua, Culpan & Menon, 2016) investigated the effect of end-effector gait training on walking speed following stroke.

The first high quality RCT (Tong et al., 2006) randomized patients with acute/subacute stroke to receive (1) gait training using the GT1 device, (2) gait training and Functional Electrical Stimulation (GT1+FES), or (3) conventional overground gait training. Walking speed was measured using the 5-meter walking test at mid-treatment (2 weeks) and post-treatment (4 weeks). A significant between-group difference was found at post-treatment, in favour of end-effector gait training vs. conventional overground gait training.
Note: Significant between-group differences in walking speed were found at both timepoints, in favour of GT1+FES vs. conventional overground gait training. There were no significant differences between end-effector gait training vs. GT1+FES.

The second high quality RCT (Ng et al., 2008) randomized patients with acute/subacute stroke to receive (1) gait training using the GT2 device, (2) gait training + Functional Electrical Stimulation (GT2+FES), or (3) conventional gait training. Walking speed was measured using the 5 meter walking test at post-treatment (4 weeks) and follow-up (6 months). A significant between-group difference was found at both timepoints, in favour of end-effector gait training vs. conventional gait training.
Note: A significant between-group difference was found at both timepoints, in favour of GT2+FES vs. conventional gait training. No significant difference was found between end-effector gait training vs. GT2+FES at either timepoint.

The third high quality cross-over RCT (Freivogel, Schmalohr & Mehrholz, 2009) randomized patients with subacute/chronic stroke to receive gait training using the LokoHelp electromechanical device or conventional treadmill/overground gait training. Walking speed was measured using the 10-meter walking test at post-treatment (6 weeks). No significant between-group difference was found.

The fourth high quality RCT (Morone et al., 2011) randomized patients with acute/subacute stroke to receive gait training using the GT1 device or conventional gait training. Patients were stratified by level of motor impairment (Motricity Index score ≤ 29: low motricity, > 29: high motricity). Walking speed was measured using the 10-meter walking test at post-treatment (4 weeks) and at discharge (average 86-102 days post-stroke according to level of impairment); discharge results were reported. No significant between-group difference was found at any time point.

The fifth high quality RCT (Chua, Culpan & Menon, 2016) randomized patients with acute/subacute stroke to receive gait training using the GT1 device or time-matched conventional physical therapy. Walking speed was measured by the 10-meter walking test at mid-treatment (4 weeks), post-treatment (8 weeks) and follow-up (12 weeks, 24 weeks, 48 weeks). No significant between-group difference was found at any time point.

Conclusion: There is conflicting evidence (Level 4) regarding the effect of end-effector gait trainers on walking speed following stroke. Two high quality RCTs found that end-effector gait trainers are more effective than a comparison intervention (conventional overground gait training), whereas three high quality RCTs found that end-effector gait trainers are not more effective than comparison interventions (conventional treadmill/overground gait training, conventional physical therapy).
Note: Two high quality RCTs found that end-effector gait training + FES is more effective than conventional overground gait training. There is no difference between end-effector gait training with/without FES.

One fair quality RCT (Kim et al., 2015) investigated the effect of an exoskeleton gait trainer on ADLs following stroke. The fair quality RCT randomized patients with subacute/chronic stroke to receive gait training using the WALKBOT device or time-matched conventional locomotor training; both groups received additional conventional locomotor training. ADLs were measured using the Korean modified Barthel Index (Grooming, Bathing, Feeding, Toilet use, Stairs, Dressing, Bowels, Bladder, Ambulation, Transfers, Total scores) at post-treatment (4 weeks) and follow-up (8 weeks). Significant between-group differences were found on only three ADL scores at both timepoints (Dressing, Ambulation, Total score), in favour of exoskeleton gait training vs. conventional locomotor training.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that an exoskeleton gait trainer is not more effective than a comparison intervention (conventional locomotor training) for improving Activities of daily living following stroke.

One fair quality RCT (Kim et al., 2015) and one non-randomized study (Dundar et al., 2014) investigated the effect of exoskeleton gait trainers on balance following stroke.

The fair quality RCT (Kim et al., 2015) randomized patients with subacute/chronic stroke to receive gait training using the WALKBOT device or time-matched conventional locomotor training; both groups received additional conventional locomotor training. Balance was measured using the Berg Balance Scale (BBS) at post-treatment (4 weeks) and follow-up (8 weeks). A significant between-group difference was found at both timepoints, in favour of exoskeleton gait training vs. conventional locomotor training.

The non-randomized retrospective study (Dundar et al., 2014) compared patients with subacute/chronic stroke who had received gait training using the Lokomat device with those who had received physical therapy. Balance was measured using the BBS at post-treatment (minimum 30 sessions). No significant between-group difference was found.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that an exoskeleton gait trainer is more effective than a comparison intervention (conventional locomotor training) for improving balance following stroke.
Note: However, a non-randomized study found that the Lokomat device was not more effective than conventional physical therapy.

One non-randomized study (Dundar et al., 2014) investigated the effect of exoskeleton gait trainers on cognition following stroke. The non-randomized retrospective study compared patients with subacute/chronic stroke who had received gait training using the Lokomat device with those who had received physical therapy. Cognition was measured using the Mini Mental Status Examination at post-treatment (minimum 30 sessions). A significant between-group difference was found, in favour of exoskeleton gait training vs. physical therapy.

Conclusion: There is limited evidence (Level 2b) from one non-randomized study that an exoskeleton gait trainer is more effective than a comparison intervention (physical therapy) for improving cognition following stroke.

One high quality RCT (Schwartz et al., 2009), one fair quality RCT (Kim et al., 2015) and one non-randomized study (Dundar et al., 2014) investigated the effect of exoskeleton gait trainers on functional ambulation following stroke.

The high quality RCT (Schwartz et al., 2009) randomized patients with acute/subacute stroke to receive gait training using the Lokomat device or time-matched conventional physical therapy for gait retraining; both groups received additional physical therapy. Functional ambulation was measured by the Functional Ambulation Category (FAC) at post-treatment (6 weeks). A significant between-group difference was found, in favour of Lokomat training vs. conventional physical therapy.

The fair quality RCT (Kim et al., 2015) randomized patients with stroke to receive gait training using the WALKBOT device or time-matched conventional locomotor training; both groups received additional conventional locomotor training. Functional ambulation was measured using the FAC at post-treatment (4 weeks) and follow-up (8 weeks). A significant between-group difference was found at both timepoints, in favour of exoskeleton gait training vs. conventional locomotor training.

The non-randomized retrospective study (Dundar et al., 2014) compared patients with subacute/chronic stroke who had received gait training using the Lokomat device with those who had received physical therapy. Functional ambulation was measured using the FAC at post-treatment (minimum 30 sessions). No significant between-group difference was found.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and one fair quality RCT that exoskeleton gait trainers are more effective than comparison interventions (physical therapy, conventional locomotor training) for improving functional ambulation following stroke.

One high quality RCT (Schwartz et al., 2009) and one non-randomized study (Dundar et al., 2014) investigated the effect of exoskeleton gait trainers on functional independence following stroke.

The high quality RCT (Schwartz et al., 2009) randomized patients with acute/subacute stroke to receive gait training using the Lokomat device or time-matched conventional physical therapy for gait retraining; both groups received additional physical therapy. Functional independence was measured by the Functional Independence Measure (FIM – Motor, Cognition) at post-treatment (6 weeks). A significant between-group difference was found in one measure (FIM – Motor), in favour of Lokomat training vs. conventional physical therapy.

The non-randomized retrospective study (Dundar et al., 2014) compared patients with subacute/chronic stroke who had received gait training using the Lokomat device with those who had received physical therapy. Functional independence was measured using the FIM at post-treatment (minimum 30 sessions). A significant between-group difference was found, in favour of exoskeleton gait training vs. physical therapy.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT and one non-randomized study that exoskeleton gait trainers are more effective than comparison interventions (physical therapy) for improving functional independence following stroke.

One fair quality RCT (Kim et al., 2015) and one non-randomized study (Dundar et al., 2014) investigated the effect of exoskeleton gait trainers on Health related quality of life (HRQoL) following stroke.

The fair quality RCT (Kim et al., 2015) randomized patients with subacute/chronic stroke to receive gait training using the WALKBOT device, or time-matched conventional locomotor training; both groups received additional conventional locomotor training. HRQoL was measured using the EuroQoL 5-dimension (EQ-5D) at post-treatment (4 weeks) and follow-up (8 weeks). No significant between-group difference was found at either timepoint.

The non-randomized retrospective study (Dundar et al., 2014) compared patients with subacute/chronic stroke who had received gait training using the Lokomat device with those who had received physical therapy. HRQoL was measured using the Medical Outcomes Study Short Form 36 (SF-36 – Physical functioning, Physical role limitations, Pain, General health, Social functioning, General mental health, Emotional role limitations, Vitality, Physical component, Mental component) at post-treatment (minimum 30 sessions). Significant between-group differences were found on all SF-36 scores, in favour of exoskeleton gait training vs. physical therapy.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that exoskeleton gait trainers are not more effective than a comparison intervention (conventional locomotor training) for improving quality of life following stroke.
Note: However, a non-randomized study found that the Lokomat device was more effective than physical therapy.

One high quality RCT (Schwartz et al., 2009) investigated the effect of an exoskeleton gait trainer on mobility following stroke. The high quality RCT randomized patients with acute/subacute stroke to receive gait training using the Lokomat device or time-matched conventional physical therapy for gait retraining; both groups received additional physical therapy. Mobility was measured by the Timed Up and Go test and the Stroke Activity Scale (Walking, Standing scores) at post-treatment (6 weeks). No significant between-group differences were found on either measure.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that an exoskeleton gait trainer is not more effective than a comparison intervention (conventional physical therapy) for improving mobility following stroke.

One non-randomized study (Dundar et al., 2014) investigated the effect of an exoskeleton gait trainer on motor recovery following stroke. The non-randomized retrospective study compared patients with subacute/chronic stroke who had received gait training using the Lokomat device with those who had received physical therapy. Motor recovery was measured using the Brunnstrom Recovery Scale (Lower extremity categories) at post-treatment (minimum 30 sessions). Significant between-group differences were found on all lower extremity categories, in favour of exoskeleton gait training vs. physical therapy.

Conclusion: There is limited evidence (Level 2b) from one non-randomized study that exoskeleton gait trainers are more effective than a comparison intervention (physical therapy) for improving motor recovery following stroke.

One fair quality RCT (Kim et al., 2015) and one non-randomized study (Dundar et al., 2014) investigated the effect of exoskeleton gait trainers on spasticity following stroke.

The fair quality RCT (Kim et al., 2015) randomized patients with subacute/chronic stroke to receive gait training using the WALKBOT device or time-matched conventional locomotor training; both groups received additional conventional locomotor training. Spasticity was measured using the Modified Ashworth Scale at post-treatment (4 weeks) and follow-up (8 weeks). No significant between-group difference was found at either timepoint.

The non-randomized retrospective study (Dundar et al., 2014) compared patients with subacute/chronic stroke who had received gait training using the Lokomat device with those who had received physical therapy. Spasticity was measured using the Modified Ashworth Scale at post-treatment (minimum 30 sessions). No significant between-group difference was found.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT and one non-randomized study that exoskeleton gait trainers are not more effective than comparison interventions (conventional locomotor training, physical therapy) for reducing spasticity following stroke.

One high quality RCT (Schwartz et al., 2009) investigated the effect of an exoskeleton gait trainer on stair climbing following stroke. The high quality RCT randomized patients with acute/subacute stroke to receive gait training using the Lokomat device or time-matched conventional physical therapy for gait retraining; both groups received additional physical therapy. Stair climbing was measured according to number of stairs climbed at post-treatment (6 weeks). A significant between-group difference was found in a subgroup of patients with high functional ambulation (Functional Ambulation Category score ≥ 3), in favour of Lokomat training vs. conventional physical therapy.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that an exoskeleton gait trainer is more effective than a comparison intervention (physical therapy) for improving stair climbing following stroke, among patients with high functional ambulation.

One high quality RCT (Schwartz et al., 2009) investigated the effect of exoskeleton gait trainers on stroke severity following stroke. The high quality RCT randomized patients with acute/subacute stroke to receive gait training using the Lokomat device, or time-matched conventional physical therapy for gait retraining; both groups received additional physical therapy. Stroke severity was measured by the National Institute of Health Stroke Scale at post-treatment (6 weeks). A significant between-group difference was found, in favour of exoskeleton gait training vs. conventional physical therapy.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that an exoskeleton gait trainer is more effective than a comparison intervention (physical therapy) for reducing stroke severity following stroke.

One high quality RCT (Schwartz et al., 2009) investigated the effect of exoskeleton gait trainers on walking endurance following stroke. The high quality RCT randomized patients with acute/subacute stroke to receive gait training using the Lokomat device or time-matched conventional physical therapy for gait retraining; both groups received additional physical therapy. Walking endurance was measured by the 2 Minute Walk Test at post-treatment (6 weeks). No significant between-group difference was found.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that an exoskeleton gait trainer is not more effective than a comparison intervention (physical therapy) for improving walking endurance following stroke.

One high quality RCT (Schwartz et al., 2009) investigated the effect of exoskeleton gait trainers on walking speed following stroke. The high quality RCT randomized patients with acute/subacute stroke to receive gait training using the Lokomat device or time-matched conventional physical therapy for gait retraining; both groups received additional physical therapy. Walking speed was measured by the 10-meter walking test at post-treatment (6 weeks). No significant between-group difference was found.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that exoskeleton gait trainers are not more effective than a comparison intervention (physical therapy) for improving walking speed following stroke.