Trial reportJMIR mHealth and uHealth2023
Clinical Study of a Wearable Remote Rehabilitation Training System for Patients With Stroke: Randomized Controlled Pilot Trial.
Trial report in JMIR mHealth and uHealth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
29 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Effectiveness of Interactive Remote Rehabilitation After Total Knee Arthroplasty: Systematic Review and Meta-Analysis of Randomized Controlled Trials.Journal of medical Internet research · 2026Pooled it
- Efficacy of remote rehabilitation therapy for upper limb dysfunction following stroke: a systematic review and meta-analysis of randomised controlled clinical trials.BMC neurology · 2026Pooled it
- Wearable Devices for Remote Monitoring of Chronic Diseases: Systematic Review.JMIR mHealth and uHealth · 2026Pooled it
- Virtual reality for stroke rehabilitation.The Cochrane database of systematic reviews · 2025Pooled it
- Effects of wearable device training on upper limb motor function in patients with stroke: a systematic review and meta-analysis.The Journal of international medical research · 2024Pooled it
- Telerehabilitation for Motor Recovery in Adults with Neurological Disorders: A Systematic Review and Meta-Analysis Across Motor Domains, Delivery Models, and Follow-Up Effects.Brain sciences · 2026Review
- Article
- A wearable sensor-based kinematic dataset collected under standardized rehabilitation tasks from 120 post-stroke patients.Scientific data · 2026Article
- Determining the adoption intention and influencing factors of telerehabilitation by people with rehabilitation needs: a cross-sectional survey.BMC public health · 2026Article
- Structural-functional connectivity coupling in motor-brain networks following acute ischemic stroke.Journal of neuroengineering and rehabilitation · 2026Article
- Distributed Precision Stroke Care: Artificial Intelligence-Driven Stroke Management Using Multimodal Sensor Data.Stroke · 2026Review
- What's New in Hand Surgery: Transformative advancements and Emerging Trends.Orthopedic reviews · 2026Article
- Artificial intelligence in rehabilitation: a review of clinical effectiveness, real-world performance, safety, and equity across modalities and settings.Frontiers in digital health · 2026Review
- Decision-centered wearable biosensors for personalized rehabilitation: integrating multimodal monitoring, artificial intelligence, and closed-loop intervention.Frontiers in bioengineering and biotechnology · 2026Review
- Smart Device-Based Therapy on Hand Motor Function Improvement in Stroke Survivors During Rehabilitation: Scoping Review.JMIR rehabilitation and assistive technologies · 2025Review
- Effects of remote rehabilitation weekend training for stroke patients in China: a randomised controlled trial protocol.BMJ open · 2025Article
- The Safety of Telerehabilitation: Systematic Review.JMIR rehabilitation and assistive technologies · 2025Review
- Effectiveness of telerehabilitation for adults with neurological conditions in low and middle income countries: A systematic review.PLOS digital health · 2025Article
- Review
- Smart Wearable Technologies for Balance Rehabilitation in Older Adults at Risk of Falls: Scoping Review and Comparative Analysis.JMIR rehabilitation and assistive technologies · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn contrast to the large and increasing number of patients with stroke, clinical rehabilitation resources cannot meet their rehabilitation needs. Especially for those discharged, ways to carry out effective rehabilitation training without the supervision of physicians and receive guidance from physicians remain urgent problems to be solved in clinical rehabilitation and have become a research hot spot at home and abroad. At present, there are many studies on home rehabilitation training based on wearable devices, Kinect, among others, but these have disadvantages (eg, complex systems, high price, and unsatisfactory rehabilitation effects).
objectiveThis study aims to design a remote intelligent rehabilitation training system based on wearable devices and human-computer interaction training tasks, and to evaluate the effectiveness and safety of the remote rehabilitation training system for nonphysician-supervised motor rehabilitation training of patients with stroke through a clinical trial study.
methodsA total of 120 inpatients with stroke having limb motor dysfunction were enrolled via a randomized, parallel-controlled method in the rehabilitation institutions, and a 3-week clinical trial was conducted in the rehabilitation hall with 60 patients in the experimental group and 60 in the control group. The patients in the experimental group used the remote rehabilitation training system for rehabilitation training and routine clinical physical therapy (PT) training and received routine drug treatment every day. The patients in the control group received routine clinical occupational therapy (OT) training and routine clinical PT training and routine drug treatment every day. At the beginning of the training (baseline) and after 3 weeks, the Fugl-Meyer Motor Function Rating scale was scored by rehabilitation physicians, and the results were compared and analyzed.
resultsStatistics were performed using SAS software (version 9.4). The total mean Fugl-Meyer score improved by 11.98 (SD 8.46; 95% CI 9.69-14.27) in the control group and 17.56 (SD 11.65; 95% CI 14.37-20.74) in the experimental group, and the difference between the 2 groups was statistically significant (P=.005). Among them, the mean Fugl-Meyer upper extremity score improved by 7.45 (SD 7.24; 95% CI 5.50-9.41) in the control group and 11.28 (SD 8.59; 95% CI 8.93-13.62) in the experimental group, and the difference between the 2 groups was statistically significant (P=.01). The mean Fugl-Meyer lower extremity score improved by 4.53 (SD 4.42; 95% CI 3.33-5.72) in the control group and 6.28 (SD 5.28; 95% CI 4.84-7.72) in the experimental group, and there was no significant difference between the 2 groups (P=.06). The test results showed that the experimental group was better than the control group, and that the patients' motor ability was improved.
conclusionsThe remote rehabilitation training system designed based on wearable devices and human-computer interaction training tasks can replace routine clinical OT training. In the future, through medical device registration certification, the system will be used without the participation of physicians or therapists, such as in rehabilitation training halls, and in remote environments, such as communities and homes.
trial registrationChinese Clinical Trial Registry ChiCTR2200061310; https://tinyurl.com/34ka2725.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.