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Abstract Number: Esoc2026a205 Wearable Sensor-assisted Rehabilitation After Stroke: a Systematic Review and Meta-analysis of Randomised Trials

Year: 2026
Type: review
Abstract: Background and aims Wearable motion-tracking devices offer objective monitoring and personalised feedback during rehabilitation, yet their overall effectiveness remains uncertain. Aim To assess whether wearable sensor-assisted rehabilitation improves motor recovery compared with conventional therapy in post-stroke patients. Methods Randomised controlled trials evaluating wearable sensors integrated into upper- or lower-limb rehabilitation programmes were included. Primary outcomes were motor function (Fugl-Meyer Assessment) and walking speed. Secondary outcomes included functional independence, balance, adherence, and adverse events. Meta-analysis used random-effects modelling. Results Seventeen trials with 2,046 participants were included. Wearable-assisted rehabilitation significantly improved motor function (MD 5.12, 95% CI 3.01–7.23; p < 0.001; I2 = 48%) and walking speed (MD 0.09 m/s, 95% CI 0.03–0.15; p = 0.004; I2 = 52%). Functional independence showed modest improvement (MD 3.06, 95% CI 0.52–5.60; p = 0.02). Balance outcomes were mixed (SMD 0.18, 95% CI –0.05 to 0.41; p = 0.12). Adverse events were rare and comparable to standard care. Adherence was consistently higher in intervention groups. Conclusions Wearable sensor-assisted rehabilitation enhances motor recovery and gait outcomes with high adherence and favourable safety, supporting its integration into contemporary stroke rehabilitation pathways. Conflict of interest all authors have has nothing to disclose
Institution: Mansoura University
Language: English
Subfield: Rehabilitation
Field: Medicine
Open Access status: hybrid
Estimated APC paid: $4,400
OpenAlex ID: W7160388926
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