Condition: Stroke · Fall · Sponsor: Seoul National University Hospital
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.
This description comes directly from the study's public registry record.
JungHyun Kim, prof · 82+1088632341 · kiking0@naver.com
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| Seoul National University Hospital | Seoul, Jongno, South Korea | Recruiting |
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Source record: clinicaltrials.gov/study/NCT06380049