Balance Rehabilitation through Robot-Assisted Gait Training in Post-Stroke Patients: A Systematic Review and...

Area of Science:

• Neurorehabilitation
• Biomedical Engineering
• Clinical Trials

Background:

• Balance impairment is a significant disability post-stroke, impacting mobility and increasing fall risk.
• Robotic gait training (RAGT) is increasingly used alongside traditional therapies.
• Evidence for RAGT's superiority, particularly for balance, remains inconclusive.

Purpose of the Study:

• To determine the efficacy of robotic gait training (RAGT) on improving balance in post-stroke survivors.
• To compare RAGT outcomes against traditional therapy.
• To explore factors influencing RAGT effectiveness through meta-regression.

Main Methods:

• Systematic literature search of PubMed, Cochrane Library, and PeDRO databases.
• Inclusion of randomized clinical trials assessing RAGT for post-stroke balance using Berg Balance Scale (BBS) or Timed Up and Go (TUG) tests.
• Meta-regression analysis to evaluate the impact of weekly sessions, session duration, and robotic device type.

Main Results:

• Eighteen trials were included in the analysis.
• RAGT showed a statistically significant improvement in BBS scores (pMD = 2.17).
• TUG test improvements favored RAGT but were not statistically significant. Treatment duration showed a significant association with TUG outcomes in meta-regression (β = -1.019, p=0.0135).

Conclusions:

• RAGT demonstrates comparable efficacy to traditional therapy for post-stroke balance.
• Combining RAGT with traditional therapy may yield superior outcomes compared to either method alone.
• Future research should focus on robot-assisted balance training, utilizing trials with stringent inclusion criteria, especially regarding time since stroke, to clarify RAGT's superiority.