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Development of a Multimodal Deep Learning Model for Pediatric Patients
Sponsor: Fu Jen Catholic University
Summary
This study aims to develop a multimodal data-driven model integrating multiple noninvasive physiological signals to assess the severity of pediatric sleep-disordered breathing, using standard clinical sleep study results as the reference.
Official title: Development of an Artificial Intelligence-Based Model for Assessing the Severity of Pediatric Obstructive Sleep Apnea
Key Details
Gender
All
Age Range
4 Years - 18 Years
Study Type
OBSERVATIONAL
Enrollment
50
Start Date
2026-09-01
Completion Date
2027-07-31
Last Updated
2026-09-04
Healthy Volunteers
No
Interventions
fingertip pulse oximeter
a small device placed on the finger to measure blood oxygen saturation and pulse rate noninvasively
pressure-sensing mattresses
using ballistocardiography for monitoring respiration and heart rate
millimeter-wave radar
using millimeter-wave radar technology based on the Doppler effect, the device continuously monitors respiratory-related chest wall movements
Locations (1)
Fu Jen Catholic University Hospital, Fu Jen Catholic University
New Taipei City, Taiwan