Supplementary Material for: Effects of Wearable Sensor-Based Balance and Gait Training on Balance, Gait, and Functional Performance in Healthy and Patient Populations: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Gordt K.
Gerhardy T.
Najafi B.
Schwenk M.
10.6084/m9.figshare.5554777.v1
https://karger.figshare.com/articles/journal_contribution/Supplementary_Material_for_Effects_of_Wearable_Sensor-Based_Balance_and_Gait_Training_on_Balance_Gait_and_Functional_Performance_in_Healthy_and_Patient_Populations_A_Systematic_Review_and_Meta-Analysis_of_Randomized_Controlled_Trials/5554777
<p><b><i>Background:</i></b> Wearable sensors (WS) can accurately measure body motion and provide interactive feedback for supporting motor learning. <b><i>Objective:</i></b>
This review aims to summarize current evidence for the effectiveness of
WS training for improving balance, gait and functional performance. <b><i>Methods:</i></b>
A systematic literature search was performed in PubMed, Cochrane, Web
of Science, and CINAHL. Randomized controlled trials (RCTs) using a WS
exercise program were included. Study quality was examined by the PEDro
scale. Meta-analyses were conducted to estimate the effects of WS
balance training on the most frequently reported outcome parameters. <b><i>Results:</i></b> Eight RCTs were included (Parkinson <i>n</i> = 2, stroke <i>n</i> = 1, Parkinson/stroke <i>n</i> = 1, peripheral neuropathy <i>n</i> = 2, frail older adults <i>n</i> = 1, healthy older adults <i>n</i> = 1). The sample size ranged from <i>n</i>
= 20 to 40. Three types of training paradigms were used: (1) static
steady-state balance training, (2) dynamic steady-state balance
training, which includes gait training, and (3) proactive balance
training. RCTs either used one type of training paradigm (type 2: <i>n</i> = 1, type 3: <i>n</i> = 3) or combined different types of training paradigms within their intervention (type 1 and 2: <i>n</i> = 2; all types: <i>n</i>
= 2). The meta-analyses revealed significant overall effects of WS
training on static steady-state balance outcomes including mediolateral
(eyes open: Hedges' <i>g</i> = 0.82, CI: 0.43-1.21; eyes closed: <i>g</i> = 0.57, CI: 0.14-0.99) and anterior-posterior sway (eyes open: <i>g</i> = 0.55, CI: 0.01-1.10; eyes closed: <i>g</i> = 0.44, CI: 0.02-0.86). No effects on habitual gait speed were found in the meta-analysis (<i>g</i>
= -0.19, CI: -0.68 to 0.29). Two RCTs reported significant improvements
for selected gait variables including single support time, and fast
gait speed. One study identified effects on proactive balance (Alternate
Step Test), but no effects were found for the Timed Up and Go test and
the Berg Balance Scale. Two studies reported positive results on
feasibility and usability. Only one study was performed in an
unsupervised setting. <b><i>Conclusion:</i></b> This review provides
evidence for a positive effect of WS training on static steady-state
balance in studies with usual care controls and studies with
conventional balance training controls. Specific gait parameters and
proactive balance measures may also be improved by WS training, yet
limited evidence is available. Heterogeneous training paradigms, small
sample sizes, and short intervention durations limit the validity of our
findings. Larger studies are required for estimating the true potential
of WS technology.</p>
2017-10-31 14:21:19
Inertial measurement unit
Force sensor
Postural balance
Gait
Biofeedback
Exergame
Systematic review