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

Recruiting Observational Study
Stroke Fall
Healthy Volunteers Welcome You do not need to have the condition being studied to take part. No Study Drug Researchers observe your health over time — no experimental treatment is given.
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At a Glance
Age
19 and older
Sex
Any
Study type
Observational
Participants needed
90 (estimated)
Sponsor
Seoul National University Hospital · Other
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About This Trial
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 hope…
Trial Locations
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Eligibility Criteria
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. parki…
Contacts

JungHyun Kim, prof

82+1088632341

kiking0@naver.com

CONTACT