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Updated: Feb 3, 2026

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients
Published on: April 18, 2025
Evaluation of a smartwatch-based intervention providing feedback of daily activity within a research-naive stroke
Sophie Lawrie1, Yun Dong2, Dax Steins1
11Centre for Movement, Occupational and Rehabilitation Sciences (MOReS), Department of Sport, Health Sciences and Social Work, Oxford Brookes University, Headington Campus, Headington Road, Gipsy Lane, Oxford, OX3 0BP UK.
Background:
The majority of stroke patients are inactive outside formal therapy sessions. Tailored activity feedback via a smartwatch has the potential to increase inpatient activity. The aim of the study was to identify the challenges and support needed by ward staff and researchers and to examine the feasibility of conducting a randomised controlled trial (RCT) using smartwatch activity monitors in research-naive rehabilitation wards. Objectives (Phase 1 and 2) were to report any challenges and support needed and determine the recruitment and retention rate, completion of outcome measures, smartwatch adherence rate, (Phase 2 only) readiness to randomise, adherence to protocol (intervention fidelity) and potential for effect.
Methods:
First admission, stroke patients (onset < 4 months) aged 40-75, able to walk 10 m prior to stroke and follow a two-stage command with sufficient cognition and vision (clinically judged) were recruited within the Second Affiliated Hospital of Anhui University of Traditional Chinese Medicine. Phase 1: a non-randomised observation phase (to allow practice of protocol)-patients received no activity feedback. Phase 2: a parallel single-blind pilot RCT. Patients were randomised into one of two groups: to receive daily activity feedback over a 9-h period or to receive no activity feedback. EQ-5D-5L, WHODAS and RMI were conducted at baseline, discharge and 3 months post-discharge. Descriptive statistics were performed on recruitment, retention, completion and activity counts as well as adherence to protocol.
Results:
Out of 470 ward admissions, 11% were recruited across the two phases, over a 30-week period. Retention rate at 3 months post-discharge was 48%. Twenty-two percent of patients dropped out post-baseline assessment, 78% completed baseline and discharge admissions, from which 62% were assessed 3 months post-discharge. Smartwatch data were received from all patients. Patients were correctly randomised into each RCT group. RCT adherence rate to wearing the smartwatch was 80%. Baseline activity was exceeded for 65% of days in the feedback group compared to 55% of days in the no feedback group.
Conclusions:
Delivery of a smartwatch RCT is feasible in a research-naive rehabilitation ward. However, frequent support and guidance of research-naive staff are required to ensure completeness of clinical assessment data and protocol adherence.
Trials Registration:
ClinicalTrials.gov Identifier, NCT02587585-30th September 2015.
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