Actively Recruiting
Predicting Fall Risk in Stroke Patients Using a Machine Learning Model and Multi-Sensor Data
Led by Seoul National University Hospital · Updated on 2025-06-02
90
Participants Needed
1
Research Sites
101 weeks
Total Duration
On this page
Sponsors
S
Seoul National University Hospital
Lead Sponsor
M
Ministry of Trade, Industry & Energy, Republic of Korea
Collaborating Sponsor
AI-Summary
What this Trial Is About
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.
CONDITIONS
Official Title
Predicting Fall Risk in Stroke Patients Using a Machine Learning Model and Multi-Sensor Data
Who Can Participate
Eligibility Criteria
You may qualify if you...
- 19 years and older
- Stroke onset less than 3 months ago
- Lower limb weakness due to stroke (MMT ≤ 4 grade)
- Cognitive ability to follow commands
- Healthy adults 19 years and older who understand the study and consent to participate
You will not qualify if you...
- Stroke recurrence
- Other neurological disorders (e.g., Parkinson's disease)
- Severely impaired cognition
- Serious or complex medical conditions (e.g., active cancer)
- Presence of cardiac pacemaker or other implanted electronic devices
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
Seoul National University Hospital
Seoul, Jongno, South Korea, 03080
Actively Recruiting
Research Team
J
JungHyun Kim, prof
CONTACT
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
0
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