ABSTRACT NUMBER: ESOC2026A205 WEARABLE SENSOR-ASSISTED REHABILITATION AFTER STROKE: A SYSTEMATIC REVIEW AND META-ANALYSIS OF RANDOMISED TRIALS

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

Authors

Institutions

Publication Details

Journal
European Stroke Journal
Published
2026-05-01
DOI
https://doi.org/10.1093/esj/aakag023.219
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ABSTRACT NUMBER: ESOC2026A205 WEARABLE SENSOR-ASSISTED REHABILITATION AFTER STROKE: A SYSTEMATIC REVIEW AND META-ANALYSIS OF RANDOMISED TRIALS

Ibrahim Serag
European Stroke Journal
Stroke Rehabilitation and Recovery
article

ABSTRACT NUMBER: ESOC2026A205 WEARABLE SENSOR-ASSISTED REHABILITATION AFTER STROKE: A SYSTEMATIC REVIEW AND META-ANALYSIS OF RANDOMISED TRIALS

Ibrahim Serag
article en

Abstract

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

European Stroke JournalVol. 11(Supplement_1)
Mansoura University (EG)
Openalex Percentile: Top 13%
Stroke Rehabilitation and Recovery
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

ABSTRACT NUMBER: ESOC2026A205 WEARABLE SENSOR-ASSISTED REHABILITATION AFTER STROKE: A SYSTEMATIC REVIEW AND META-ANALYSIS OF RANDOMISED TRIALS — Ibrahim Serag · European Stroke Journal (2026) | TGRS Research Map | TGRS