Edited by: Marco Iosa, Fondazione Santa Lucia, Italy
Reviewed by: Federica Tamburella, Fondazione Santa Lucia, Italy; Alessandra Pompa, Fondazione Santa Lucia, Italy
*Correspondence: Nicola Smania, Department of Neurological and Movement Sciences, Neuromotor and Cognitive Rehabilitation Research Center (CRRNC), University of Verona, P.le L.A. Scuro 10, 37134, Verona, Italy e-mail:
This article was submitted to the journal Frontiers in Human Neuroscience.
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Multiple Sclerosis (MS) is a chronic disease of the central nervous system characterized by a progressive decline in various neurologic functions such as vision, sensation, coordination and balance, muscle strength and tone (Nelson et al.,
Data from studies on healthy subjects showed that gait involves a complex interplay between cortical and spinal circuits. A full review of neural correlates of walking control is beyond this perspective. Nevertheless, the overall evidence that locomotion control relies on the integrity of feedback and feed forward mechanisms of movement control (including postural adjustments) (Dietz et al.,
Although a wide range of movement control dysfunctions might contribute to gait impairment in people with MS, balance disorders are thought to contribute to most of MS walking-related disabilities. Indeed, they negatively influence gait performance by reducing gait velocity, shortening steps length, increasing double support time and decreasing single support and swing times (Cameron and Lord,
Several studies investigating locomotion disturbances in patients with MS showed that both MS-specific reorganization of the posture control system (Corradini et al.,
As a whole, these evidence support that specific treatments aimed at improving the efficiency of postural reactions can improve gait quality and might potentially contribute to an improvement in activity, community participation, and quality of life in people with MS (Cameron et al.,
Rehabilitation studies have shown that different approaches may be useful in treating balance disturbances stemming from neurological dysfunctions. Conventional balance rehabilitation strategies proved to be effective in both stroke and Parkinson disease (Smania et al.,
The aim of this study was to compare the effectiveness of end-effector robot-assisted gait training (RAGT) and sensory integration balance training (SIBT) in improving walking and balance performance in patients with MS. The hypothesis was that both types of training might promote central neural processes involved in feedback and feed forward control of gait and balance. The rationale behind the study is twofold. First, it would further explore the potential field of application of new technological devices, which are increasingly being used in clinical practice even though their mechanisms of action are still unknown. Second, it would be relevant to find new approaches which allow training patients in a safe and efficient manner even when neurological condition is severe.
A single blind RCT comparing the effects between the experimental (RAGT) and control group (SIBT) on walking and balance disorders was performed (allocation ratio 1:1). The examiner was blinded to group assignment.
Outpatients with relapsing remitting or secondary progressive MS (Polman et al.,
Prior to the start of the study, authors designed RAGT and SIBT protocols and instructed two treating physiotherapists, one for the RAGT group and the other for the SIBT group. Treatment procedures consisted of 12 individual sessions of 50 min, twice weekly (Monday and Wednesday or Tuesday and Friday) for six consecutive weeks. Both treatments were tailored to suit each patient's ability and task complexity was progressively increased as the patient improved. Patients were not allowed to receive other physiotherapy during the study, but were given no other activity restrictions. Training procedures were administered in the morning around 10 AM, to ensure that fatigue did not influence the patient's performance. Participants were allowed to wear their usual footwear and orthoses.
The RAGT group was treated by means of the electromechanical Gait Trainer GT1 (Reha-Stim, Berlin, Germany) (Hesse et al.,
The SIBT patients underwent a specific training program aimed at improving the ability to integrate multisensory inputs during balance responses (Nichols,
An examiner, who was blinded to the patients' group allocation, performed all evaluations. Primary and secondary outcomes were measured before (T0), after treatment (T1) and at 1-month follow-up (T2). Patients were examined around 10 AM in the morning to reduce the effect of fatigue frequently reported later in the day.
The patient is tested in two consecutive conditions (eyes-open and eyes-closed) each lasting 30-s according to Cattaneo and Jonsdottir's protocol (Cattaneo and Jonsdottir,
The following spatiotemporal gait parameters were evaluated by means of GAITRite System: cadence (step/min), step length (cm), single support time (% of cycle) and double support time (% of cycle) (Menz et al.,
After screening, an independent blinded collaborator who was not involved in the treatment or care of patients, randomly assigned eligible patients to the RAGT or SIBT according to a simple software-generated randomization scheme (Dallal,
The Mann-Whitney test was used for testing differences between groups at baseline. The Friedman's ANOVA was used to analyse within-group changes in performance overtime, whilst the Wilcoxon signed rank tests to compare within-group changes from baseline/post-treatment and baseline/follow-up measures. The Mann-Whitney test was used for between-group comparisons. For this purpose, we computed the differences (Δ) between post- and pre-treatment performance and between follow-up and pre-treatment performance for all outcome measures. We set the alpha level for significance at 0.05, however, to adjust for multiple comparisons we used a Bonferroni correction (alpha level = 0.025). Descriptive analysis was used to evaluate the effect size measures between the 2 independent groups (Cohen's
Thirty-two patients were evaluated for eligibility between September 2011 and November 2013. Five patients were excluded because they did not meet the inclusion criteria and 1 declined to participate. Thus, 26 patients were randomly allocated to the RAGT (
Two patients in the RAGT and 2 in the SIBT did not complete the allocated intervention due to difficulty in transportation or medical complications to treatment sessions (Figure
Age (years) | 50.83 (8.42) | 50.1 (6.29) | 0.640 (−468) |
Range | 38–63 | 42–60 | |
Sex (Male/Female) | 5/7 | 1/9 | |
EDSS | 3.96 (0.75) | 4,35 (0.67) | 0.101 (−1.640) |
Range | 3–5.5 | 3.5–5.5 | |
Disease duration (years) | 13.5 (7.60) | 14.9 (8.68) | 0.731 (−0.344) |
Range | 5–34 | 5–27 | |
Gait speed (cm/s) | 79.42 (21.14) | 81.31 (16.81) | 0.895 (−0.132) |
BBS (0–56) | 47.17 (5.27) | 46.50 (6.69) | 0.921 (−0.100) |
ABC scale (0–100) | 59.68 (11.31) | 61.90 (7.06) | 0.226 (−1.210) |
SOT S. surface (0–150) | |||
EO | 118.73 (39.52) | 114.56 (38.66) | 0.691 (−0.398) |
EC | 63.37 (28.12) | 52.23 (24.65) | 0.210 (−1.253) |
Dome | 62.75 (40.07) | 57.89 (31.97) | 0.895 (−0.132) |
SOT C. surface (0–150) | |||
EO | 96.48 (37.76) | 110.43 (23.27) | 0.322 (−0.990) |
EC | 50.59 (32.95) | 39.06 (16.82) | 0.598 (−0.528) |
Dome | 58.52 (45.85) | 30.96 (15.80) | 0.176 (−1.352) |
Sway area (mm2) | 83.48 (83.53) | 128.54 (84.03) | 0.121 (−1.550) |
Length CoP (mm) | 499.66 (499.0) | 504.60 (408.06) | 0.644 (−0.462) |
Sway area (mm2) | 250.48 (261.99) | 509.22 (342.79) | 0.065 (−1.846) |
Length CoP (mm) | 951.66 (1045.29) | 1157.90 (951.54) | 0.429 (−0.791) |
Cadence (step/min) | 117.13 (28.22) | 106.32 (37.49) | 0.138 (−1.481) |
SL (cm) | 56.88 (19.57) | 58.62 (25.99) | 0.843 (−0.198) |
SS time (% of cycle) | 33.85 (4.23) | 40.84 (16.49) | 0.235 (−1.187) |
DS time (% of cycle) | 31.30 (5.48) | 39.54 (14.35) | 0.187 (−1.319) |
FSS (1–7) | 4.40 (1.386) | 4.03 (2.25) | 0.598 (−0.528) |
MSQOL-54 PHC (0–100) | 64.17 (6.53) | 59.59 (10.67) | 0.288 (−1.061) |
MSQOL-54 MHC (0–100) | 59.01 (21.69) | 59.51 (20.70) | 1.000 (0.000) |
Multiple separate independent-sample Mann-Whitney tests showed that there was no significant difference between groups as to age, EDSS, disease duration, and all baseline clinical measures at T0 (Table
Between groups comparisons showed no significant changes on primary outcome measures over time (Table
Gait speed (cm/s) | 0.644 (0.10) | 0.895 (0.02) |
BBS (0–56) | 0.547 (0.13) | 0.091 (0.28) |
ABC scale (0–100) | 0.741 (0.09) | 0.692 (0.08) |
SOT—S. surface (0–150) EO | 0.197 (−0.34) | 0.075 (−0.37) |
EC | 0.947 (−0.13) | 0.210 (−0.27) |
Dome | 0.187 (0.29) | 0.553 (0.15) |
SOT—C. surface (0–150) EO | 0.843 (−0.05) | 0.553 (0.01) |
EC | 0.644 (−0.12) | 0.291 (−0.30) |
Dome | 0.129 (−0.31) | 0.048 (−0.32) |
Sway area (mm2) | 0.817 (−0.20) | 0.553 (−0.10) |
Length CoP (mm) | 0.468 (−0.05) | 0.895 (−0.10) |
Sway area (mm2) | 0.210 (0.20) | 0.598 (0.10) |
Length CoP (mm) | 0.767 (0.20) | 0.895 (−0.03) |
Cadence (step/min) | 0.322 (−0.22) | 0.339 (−0.25) |
SL (cm) | 0.235 (−0.11) | 0.644 (0.02) |
SS time (% of cycle) | 0.742 (0.15) | 0.974 (−0.15) |
DS time (% of cycle) | 0.065 (0.41) | 0.166 (0.15) |
FSS (1–7) | 0.276 (0.18) | 0.391 (0.08) |
MSQOL-54 PHC (0–100) | 0.261 (−0.27) | 0.869 (−0.06) |
MSQOL-54 MHC (0–100) | 0.667 (−0.15) | 0.235 (0.07) |
In the RAGT group we found within-group changes (Friedman' ANOVA) approaching significance on gait speed (
Gait speed (cm/s) | 79.42 (21.14) | 81.31 (16.81) | 86.49 (23.05) | 85.11 (12.96) | 86.04 (21.67) | 87.44 (13.93) | 0.117 (−1.67; 15.81) | 0.050 (−2.17; 15.41) | 0.515 (−8.51; 16.10) | 0.333 (−6.63; 18.87) |
BBS (0−56) | 47.17 (5.27) | 46.50 (6.69) | 52.58 (2.64) | 50.70 (5.74) | 53.33 (2.06) | 50.00 (5.46) | 0.007 (1.95; 8.88) |
0.002 (3.07; 9.25) |
0.007 (1.38; 7.01) |
0.018 (0.38; 6.61) |
ABC scale (0−100) | 59.68 (11.31) | 61.90 (7.06) | 70.79 (11.04) | 72.14 (10.24) | 69.09 (10.38) | 70.63 (9.72) | 0.010 (2.81; 19.41) |
0.023 (1.88; 16.94) |
0.008 (3.94; 14.48) |
0.012 (3.67; 12.04) |
SOT (0−150)—S. surface EO | 118.73 (39.52) | 114.56 (38.66) | 125.76 (34.80) | 143.89 (10.88) | 123.22 (35.09) | 137.61 (24.38) | 0.86 (−2.82; 16.88) | 0.386 (−5.38; 14.37) | 0.015 (0.55; 58.09) |
0.021 (2.49; 43.59) |
EC | 63.37 (28.12) | 52.23 (24.65) | 71.53 (30.50) | 65.82 (20.40) | 73.83 (31.19) | 79.13 (37.07) | 0.136 (−7.20; 23.52) | 0.209 (−10.08; 30.97) | 0.047 (2.01; 25.15) | 0.009 (7.70; 46.09) |
Dome | 62.75 (40.07) | 57.89 (31.97) | 77.15 (38.17) | 59.36 (27.36) | 76.77 (36.18) | 65.83 (40.28) | 0.022 (1.27; 27.51) |
0.059 (0.30; 27.72) | 0.878 (−14.54; 17.47) | 0.241 (−5.58; 21.46) |
SOT (0−150)—C. surface EO | 96.48 (37.76) | 110.43 (23.27) | 100.92 (38.83) | 116.56 (18.98) | 95.73 (37.12) | 109.46 (36.75) | 0.285 (−7.10; 15.99) | 0.790 (−11.97; 10.46) | 0.260 (−4.13; 16.37) | 0.445 (−24.38; 22.44) |
EC | 50.59 (32.95) | 39.06 (16.82) | 63.03 (35.75) | 58.86 (18.41) | 56.70 (34.49) | 64.90 (35.38) | 0.272 (−12.55; 37.43) | 0.272 (−15.14; 27.36) | 0.013 (6.82; 32.77) |
0.028 (5.10; 46.58) |
Dome | 58.52 (45.85) | 30.96 (15.80) | 63.33 (37.54) | 51.33 (27.06) | 56.23 (37.13) | 48.87 (33.81) | 0.583 (−14.19; 23.81) | 0.695 (−25.61; 21.02) | 0.007 (8.30; 32.43) |
0.009 (3.24; 32.59) |
Between groups comparisons showed significant differences on performance at SOT compliant surface-dome condition (
In the RAGT group within-group significant changes (Friedman' ANOVA) on ABC (
In the SIBT group within-group significant changes (Friedman' ANOVA) on ABC (
Sway area (mm2) | 83.48 (83.53) | 128.54 (84.03) | 64.55 (48.67) | 141.44 (124.10) | 120.40 (108.76) | 165.21 (133.04) | 0.182 (−50.33; 12.50) | 0.594 (−26.66; 60.37) | 0.799 (−55.69; 81.49) | 0.683 (−54.53; 127.87) |
Length CoP (mm) | 499.66 (499.01) | 504.60 (408.06) | 398.16 (354.27) | 422.70 (369.64) | 369.08 (342.85) | 413.77 (336.63) | 0.055 (−227.26; 24.26) | 0.182 (−441.53; 118.84) | 0.241 (−234.92; 71.12) | 0.169 (−245.09; 63.44) |
Sway area (mm2) | 250.48 (261.99) | 509.22 (342.79) | 243.32 (230.54) | 407.14 (311.95) | 266.43 (216.58) | 480.28 (330.37) | 0.657 (−136.77; 122.44) | 0.530 (−103.80; 135.69) | 0.169 (−282.46; 78.30) | 0.959 (−200.36; 142.48) |
Length CoP (mm) | 951.67 (1045.29) | 1157.9 (951.54) | 935.17 (1146.48) | 1035.4 (993.74) | 797.00 (736.14) | 1154.78 (1053.15) | 0.480 (−135.59; 102.59) | 0.424 (−451.72; 142.38) | 0.285 (−352.55; 107.55) | 0.953 (−541.29; 304.09) |
Cadence (step/min) | 117.13 (28.22) | 106.32 (37.49) | 114.45 (24.75) | 107.29 (42.01) | 114.53 (33.78) | 111.07 (40.04) | 0.959 (−35.39; 11.40) | 0.959 (−37.47; 13.61) | 0.859 (−12.43; 14.17) | 0.374 (−8.46; 17.02) |
SL (cm) | 56.88 (19.57) | 58.62 (25.99) | 62.39 (22.04) | 65.95 (28.44) | 59.49 (20.06) | 60.99 (27.02) | 0.084 (−0.32; 11.34) | 0.028 (−0.00; 5.23) | 0.005 (2.09; 12.56) |
0.508 (−3.80; 8.52) |
SS time (% of cycle) | 33.85 (4.23) | 40.84 (16.49) | 34.20 (4.39) | 39.44 (16.84) | 33.48 (4.93) | 38.01 (10.17) | 0.814 (−1.79; 2.48) | 0.799 (−14.07; 2.15) | 0.799 (−6.65; 3.85) | 0.508 (−8.13; 2.46) |
DS time (% of cycle) | 31.30 (5.48) | 39.54 (14.35) | 29.79 (4.96) | 31.40 (12.61) | 28.49 (5.60) | 28.03 (5.88) | 0.084 (−3.42;.40) | 0.074 (−16.38; 1.26) | 0.005 (−15.25; −1.01) |
0.005 (−20.27; −2.73) |
FSS (1–7) | 4.40 (1.38) | 4.03 (2.25) | 3.96 (1.17) | 3.02 (1.50) | 4.13 (1.81) | 3.12 (1.84) | 0.530 (−1.60;.73) | 0.789 (−2.07;.84) | 0.036 (−1.97; −0.05) | 0.059 (−1.89;.07) |
MSQOL−54 PHC (0–100) | 64.17 (6.53) | 59.59 (10.67) | 60.84 (9.01) | 61.34 (8.16) | 60.79 (5.85) | 57.30 (9.60) | 0.507 (−8.04; 2.51) | 0.169 (−7.20; 1.57) | 0.214 (−3.60; 6.74) | 0.214 (−5.75; 1.63) |
MSQOL−54 MHC (0–100) | 59.01 (21.69) | 59.51 (20.7) | 61.11 (19.58) | 65.24 (15.34) | 63.82 (15.01) | 62.10 (18.38) | 0.574 (−3.78; 7.28) | 0.093 (−1.79; 9.79) | 0.314 (−4.55; 14.87) | 0.953 (−7.21; 11.88) |
Results showed that RAGT and SIBT might improve step length, postural stability and the level of balance confidence perceived while performing daily activities in patients with MS. These training effects may be maintained for at least 1 month post-treatment.
So far many approaches have been proposed to improve walking and balance in people with MS (Armutlu et al.,
This is the first pilot study that evaluates the effects of an end-effector RAGT compared to a SIBT in walking and balance performance in patients with MS.
It is worthy to note that in all previous studies an exoskeleton device (Lokomat) was used as RAGT, and the control group consisted of over ground walking training. Thus, differences with our study were twofold. On one hand, the type of device used as RAGT was an end-effector device (Gang Trainer GT1) and on the other hand the type of treatment used as “control” condition was specific SIBT.
The Gang Trainer GT1 (Hesse et al.,
Interestingly, significant changes in the GT1 group were found also on postural stability. This can be considered as one of the most important findings in our study because the majority of the existing literature on RAGT in MS patients does not evaluate this outcome. The issue of balance recovery is very relevant in MS rehabilitation studies (Cameron and Lord,
Walking can be seen as a repeated sequence of balance challenges (Cameron and Lord,
Currently, interventions that specifically address proprioceptive and/or central processing deficits are likely to be particularly effective in MS patients. Proprioceptive information, in fact, plays a crucial role with respect to the knowledge on external environment (i.e., body position knowledge, sensorimotor control of functional joint stability and feedback postural adjustments) and in motor control during internally generated motor commands (internal model). The concept behind the study is that the task-specific balance training should improve gait performance and vice versa because postural control is essential for walking.
Our findings cannot be fully discussed with those by Straudi (Straudi et al.,
A possible explanation of the balance improvements is that GT1 approach act as a form of “destabilization training.” For the first time in literature we might introduce the concept of “task specific balance training” by end-effector RAGT.
This training might play a role for reinforcing the neuronal circuits that contribute to postural control. In particular, RAGT represents an external force that could interfere with the abnormal experience of balance and gait. An end-effector system may represent a more suitable device for this purpose. It enables wheelchair-bound subjects to practice a gait-like movement with minimal assistance. The harness-secured patients are positioned on 2 footplates, whose movements simulate stance and swing in a highly physiological manner. In this context the patient has a reduced number of constraints acting at different lower limb levels. A reduced number of constraints and more freedom during exercise, especially for pelvic movements, may be an optimal environment for learning. Similar results with an end-effector system were found in patients affected by Parkinson's disease (Picelli et al.,
This is a significant result, given that MS patients suffer from balance disorders very early during the disease even when gait disorders are minimal. From a clinical perspective having another rehabilitation strategy for these high disabling disorders is very relevant. Nevertheless future studies on larger sample and involving patients stratified by EDSS would allow us to better understand which approach (robot assisted balance training or SIBT) and for which patients would be more useful to improve balance task related domains and/or gait related domains. MS patients with different degrees of disability require different needs in terms of treatment's type, intensity, and frequency.
As to SIBT effects, significant improvements on BBS and ABC paralleled significant effects in sensory-motor integration ability and dynamic balance performance. Indeed, patients in the SIBT group showed improvements during SOT conditions (stable surface-opened eyes and closed eyes) and in most difficult performance (compliant surface-closed eyes and dome conditions). In healthy subjects balance control is a complex process involving the reception and the integration of visual, sensorimotor, and vestibular sensory inputs, which allows the planning and execution of the movements required to maintain balance during upright posture and gait (Merfeld et al.,
Several studies evaluated the efficacy of rehabilitation for improving balance in people with MS (Armutlu et al.,
An important finding that required discussion was the no statistically significant differences between the end-effector RAGT and the SIBT in primary outcome measures. Moreover, for improvements in secondary outcome measures, between-group differences were in favor of the SIBT for one SOT condition (compliant surface-dome). According to our hypothesis, these results support the assumption that this form of RAGT, which practices a gait-like movement with minimal assistance, allows patients to train postural and gait control. Many advantages that further support the use of end-effector RAGT may be acknowledged: the patient may be trained safely owing to body harness, the complexity of the tasks might be improved over time by changing the amount of body weight support and, finally, it does not necessarily require a one-by-one physical therapist assistance. Further, recent work has demonstrated that end-effector RAGT enables patients repetitive practice of stair climbing, which is considered a more demanding balance task than gait (Hesse et al.,
The point to use end-effector RAGT and SIBT in people with MS is that overall evidence supports that these patients have CPAs and APAs as well as sensory integration deficits leading to “internal representation” of motor and sensory signals impairments.
People with MS have a strong delay in CPAs onset in terms of magnitude and velocity (Cameron et al.,
Another important mechanism involved in gait encompasses afferent input. Widespread research revealed afferent inputs are involved in motor output shaping during walking (Dietz et al.,
Limitations of the present study are the small sample size, the clinical heterogeneity of patients according to EDSS score, the lack of patients' stratification by neurological severity, the lack of a follow-up assessment at 3 or more months after training and the lack of assessment of CPAs and APAs with electromyography. Future studies should determine frequency, duration, and other important aspects of RAGT parameters, such as speed, and need for body weight support. Finally, postural destabilizations and sensory strategies might add a substantial value to ongoing therapy.
Treatment of gait and balance dysfunction in people with MS has developed significantly in recent years. Studies demonstrated the potential effect of various interventions for improving walking and balance disorders, with benefits reported also by the patients. However, there are cloudy hypotheses that are driving this research area. To speed up the progress in this field of research, several crucial points should taken into account when planning future studies (Zackowski et al.,
To perform randomized controlled trial on larger sample in order to evaluate SIBT and end-effector RAGT effectiveness in MS patients. In our opinion, the RAGT devised for this purpose should be an end-effector one in order to improve gait and balance too.
To evaluate the effects of treatments combining SIBT and end-effector RAGT.
To develop new technological software that may include for instance exercises with sensory augmentations for the impaired proprioception and/or with the use of surfaces and vision manipulation aimed at improving somatosensory integration processes (Elwishy,
To couple visual information and feedback in order to improve the awareness of disturbed walking and to engage actively the patients' participation and motivation during training.
To amplify the patient's movement errors (Emken and Reinkensmeyer,
This is the first study comparing the effects on walking and balances between the end-effector RAGT and SIBT. These preliminary results suggest that the end-effector RAGT training may act as task-specific balance training in order to promote central neural processes involved in gait and balance control.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
This work was supported by funding from the Italian Multiple Sclerosis Foundation grant (FISM 2009/R/27).
All authors gave a substantial contribution to the design of the work and acquisition, analysis, interpretation of data; Marialuisa Gandolfi conceived of the study, carried out the studies, data acquisition, analysis and interpretation, drafted the manuscript. Christian Geroin and Alessandro Picelli carried out the studies, data acquisition, analysis and interpretation, drafted the manuscript and performed the statistical analysis. Daniele Munari carried out the studies, data acquisition and interpretation, drafted the manuscript. Nicola Smania, Andreas Waldner, Stefano Tamburin, and Fabio Marchioretto conceived of the study, participated in its design and coordination, and assisted in drafting the manuscript. All authors read and approved the final manuscript. All authors declare to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
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