Robotic locomotor training in rehabilitation
Table III. Spasticity assessments in individuals with spinal cord injury (SCI) using robotic locomotor training (RLT)
Clinical
Self-reported
Spinal cord assessment
tool for spastic reflexes
Author (reference)
Benson et al. (2016) (7)
729
Esquenazi et al. (2012)
(18)
Kressler et al. (2)
T0–T1 = no change*
Platz et al. (2016) (25)
Stampacchia et al. (2016)
(26)
Modified Ashworth Scale
Numeric rating scale (0–10)
2 participants = mild spasticity pre-session was reduced
post-sessions (mean decrease of 0.71)*
T0–T1 = spasticity reduced*
T0–T1 = 3/11 reported reduced spasticity;
none reported increased spasticity*
Post-trial = none to mild spasticity
reported*
T0–T1 = no change*
Pre-session = 2.0 [0.0–4.5]
Total lower limb score for 3 segments:
Pre-session = 4.0 [0.0–10.7] Post-session = 0.0 [0.0–1.5]
Post-session = 2.0 [0.0–5.2] (p < 0.001)
(p < 0.001)
T0: pre-intervention; T1: post-intervention; significance: p < 0.05.
*Studies with missing original data or level of significance.
Quality of evidence Gait parameters
As a consequence of important limitations in study
design, inconsistency and lack of directness in the
results, the overall quality of evidence was judged
to be very low using the GRADE system (Table VI).
Further research on RLT for SCI rehabilitation is highly
likely to have an important impact on confidence in
the estimate of effect. The meta-analyses performed on the relevant included
studies showed that RLT can be used as an effective
rehabilitation method to significantly improve walking
capacity (p < 0.001). Positive pooled effects were found
for the 6MWT, 10MWT and TUG meta-analyses
from pre to post RLT interventions (Figs 2–4). Other
studies have shown similar positive effects of RLT on
walking function in several neurological diagnoses,
but the mechanism behind this restored function is
still debated (15).
Walking function is correlated with an increase in
session number (p < 0.001), as participants were able to
walk greater distances with improved velocities over
more training sessions (2, 7, 18, 20, 21). This general
trend of improved walking capacity suggests a training
effect due to the increased proficiency in ambulating
within the exoskeleton device over time (4). Longer
DISCUSSION
This systematic review aimed to provide an overview
of the current evidence on RLT rehabilitation after
SCI, focusing on walking performance and secon-
dary measures including cardiovascular demands and
health-related benefits. A total of 27 non-randomized,
non-comparative observational studies, representing
308 participants, were included in the analysis.
Table IV. Pain assessments in individuals with spinal cord injury (SCI) using robotic locomotor training (RLT)
Author (reference) Visual analogue scale (VAS)
Benson et al. (2016) (7)
Esquenazi et al. (2012) (18) Pre – post sessions = improved pain intensity (VAS = +0.19)*
T0–T1 = 5/12 participants reported a combined 28× that pain
was reduced*
Post-session = No significant pain reported*
Kolakowsky-Hayner et al. (2013) (4)
Kressler et al. (2014) (2)
Sale et al. (2016) (15)
Numeric rating scale (NRS 0–6)
T0–T1 = reduction in pain severity scores (mean
of–1.3 to 1.7 difference) (p < 0.05)*
T0 = 3.333±4.041
T1 = 3.00±3.464
Sale et al. (2018) (16)
No significant change (p > 0.05)
T0 = 1.00±2.83
T1 = 0.88±2.47
Stampacchia et al. (2016) (26)
No significant change (p > 0.05)
Pre-session: 6.0 [4.5–7.0]
Post-session: 2.0 [0.0–4.0]
Zeilig et al. (2012) (19)
(p = 0.002)
Pre-session = 1.77±0.92
Post-session = 1.71±1.02
No significant change (p > 0.05)
*Studies with missing original data or level of significance.
T0: pre-intervention; T1: post-intervention; significance: p > 0.05.
J Rehabil Med 51, 2019