Does robot-assisted gait rehabilitation improve balance in stroke patients? A systematic review.
The aim of this systematic review was to summarize the improvements in balance after robot-assisted gait training (RAGT) in stroke patients. Two databases were searched: PubMed and Web of Knowledge. The most important key words are "stroke," "RAGT," "balance," "Lokomat," and "gait trainer." Studies were included if stroke patients were involved in RAGT protocols, and balance was determined as an outcome measurement. The articles were checked for methodological quality by 2 reviewers (Cohen's κ = 0.72). Nine studies were included (7 true experimental and 2 pre-experimental studies; methodological quality score, 56%-81%). In total, 229 subacute or chronic stroke patients (70.5% male) were involved in RAGT (3 to 5 times per week, 3 to 10 weeks, 12 to 25 sessions). In 5 studies, the gait trainer was used; in 2, the Lokomat was used; in 1 study, a single-joint wearable knee orthosis was used; and in 1 study, the AutoAmbulator was used. Eight studies compared RAGT with other gait rehabilitation methods. Significant improvements (no to large effect sizes, Cohen's d = 0.01 to 3.01) in balance scores measured with the Berg Balance Scale, the Tinetti test, postural sway tests, and the Timed Up and Go test were found after RAGT. No significant differences in balance between the intervention and control groups were reported. RAGT can lead to improvements in balance in stroke patients; however, it is not clear whether the improvements are greater compared with those associated with other gait rehabilitation methods. Because a limited number of studies are available, more specific research (eg, randomized controlled trials with larger, specific populations) is necessary to draw stronger conclusions.
Faculty of Physical Education and Physiotherapy, Advanced Rehabilitation Technology and Science (ARTS), Vrije Universiteit Brussel, Brussels, Belgium Faculty of Physical Education and Physiotherapy, Rehabilitation Research, Vrije Universiteit Brussel, Brussels, Belgium Center for Neuroscience, Vrije Universiteit Brussel, Brussels, Belgium.
Eva
E
Swinnen
Faculty of Physical Education and Physiotherapy, Rehabilitation Research, Vrije Universiteit Brussel, Brussels, Belgium.
David
D
Beckwée
Faculty of Physical Education and Physiotherapy, Advanced Rehabilitation Technology and Science (ARTS), Vrije Universiteit Brussel, Brussels, Belgium Center for Neuroscience, Vrije Universiteit Brussel, Brussels, Belgium.
Romain
R
Meeusen
Faculty of Physical Education and Physiotherapy, Advanced Rehabilitation Technology and Science (ARTS), Vrije Universiteit Brussel, Brussels, Belgium Physiotherapy, University College Thim van der Laan, Landquart, Switzerland.
Jean-Pierre
JP
Baeyens
Faculty of Physical Education and Physiotherapy, Advanced Rehabilitation Technology and Science (ARTS), Vrije Universiteit Brussel, Brussels, Belgium Faculty of Physical Education and Physiotherapy, Rehabilitation Research, Vrije Universiteit Brussel, Brussels, Belgium Center for Neuroscience, Vrije Universiteit Brussel, Brussels, Belgium.
Eric
E
Kerckhofs
D000368:Aged; D005081:Exercise Therapy / Q000379:methods; D005260:Female; D020233:Gait Disorders, Neurologic / Q000209:etiology / Q000503:physiopathology / Q000534:rehabilitation*; D006801:Humans; D008297:Male; D008875:Middle Aged; D026741:Physical Therapy Modalities; D004856:Postural Balance; D012107:Research Design; D012371:Robotics; D000071939:Stroke Rehabilitation; D016896:Treatment Outcome
Berg Balance Scale; balance; gait; robot assistance; stroke