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Predicting Fall Risk in Stroke Patients Using a Machine Learning Model and Multi-Sensor Data

Recruitingn/aAges 19 Years - anyAllSeoul National University Hospital
NCT06380049 on ClinicalTrials.gov ↗
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In plain words

What the trial is, and whether it could suit you

The study assesses a machine learning model developed to predict fall risk among stroke patients using multi-sensor signals. This prospective, multicenter, open-label, sponsor-initiated confirmatory trial aims to validate the safety and efficacy of the model which utilizes electromyography (EMG) signals to categorize patients into high-risk or low-risk fall categories. The innovative approach hopes to offer a predictive tool that enhances preventative strategies in clinical settings, potentially reducing fall-related injuries in stroke survivors.

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📋 Eligibility rules (as published)
Stroke Participants Inclusion Criteria: * 19 years and older * the onset of the stroke is less than 3months ago * Lower extremity weakness due to stroke (MMT =\< 4 grade) * Cognitive ability to follow commands Exclusion Criteria: * stroke recurrence * other neurological abnormalities (e.g. parkinson's disease). * severely impaired cognition * serious and complex medical conditions(e.g. active cancer) * cardiac pacemaker or other implanted electronic system Health Participants Inclusion Criteria: * 19 years and older * Individuals who fully understand the necessity of the study and have voluntarily consented to participate as subjects Exclusion Criteria: * other neurological abnormalities (e.g. parkinson's disease). * severely impaired cognition * serious and complex medical conditions(e.g. active cancer) * cardiac pacemaker or other implanted electronic system
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What it tests

  • EMG Analysis Software
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Where

1 site
Seoul National University Hospital
Seoul, South Korea
🤝 Taking part is your choice, and you can leave at any time. Only the trial team can confirm you are eligible — always decide together with your own doctor.
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