Development of a Multimodal Deep Learning Model for Pediatric Patients

September 1, 2026 updated by: Ke-Yun, Chao, Fu Jen Catholic University

Development of an Artificial Intelligence-Based Model for Assessing the Severity of Pediatric Obstructive Sleep Apnea

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.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Detailed Description

Pediatric obstructive sleep apnea may affect growth, development, cognitive function, and overall health. Although polysomnography is commonly used for clinical assessment, its application may be limited by time, cost, and accessibility. Recent advances in noninvasive monitoring technologies have provided new possibilities for sleep-related assessment. This study will collect and integrate multiple physiological signals from pediatric participants undergoing routine sleep examinations and to develop a data-driven model for evaluating sleep-related respiratory conditions. Clinical examination results will be used as the reference for model development and validation. The findings of this study are expected to support the development of a convenient and noninvasive approach for pediatric sleep assessment and may provide a reference for future clinical and home-based applications.

Study Type

Observational

Enrollment (Estimated)

50

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • Taiwan
      • New Taipei City, Taiwan, 24352
        • Fu Jen Catholic University Hospital, Fu Jen Catholic University
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

patient of affiliated university hospital

Description

Inclusion Criteria:

  • Individuals with clinical suspicion of obstructive sleep apnea who are referred for polysomnography

Exclusion Criteria:

  • Intolerance to a fingertip or wrap-around pulse oximeter
  • Presence of significant structural abnormalities of the upper airway
  • Cardiac arrhythmia
  • Neuromuscular disease
  • Hospitalization within the previous one month

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Time Frame
the correlation among the apnea-hypopnea index, millimeter-wave radar signals, and ballistocardiography waveforms
Time Frame: one night
one night

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Fu Jen Catholic University

Investigators

  • Principal Investigator: Ke-Yun Chao, PhD, Fu Jen Catholic University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

September 1, 2026

Primary Completion (Estimated)

July 31, 2027

Study Completion (Estimated)

July 31, 2027

Study Registration Dates

First Submitted

September 1, 2026

First Submitted That Met QC Criteria

September 1, 2026

First Posted (Actual)

September 4, 2026

Study Record Updates

Last Update Posted (Actual)

September 4, 2026

Last Update Submitted That Met QC Criteria

September 1, 2026

Last Verified

August 1, 2026

More Information

Terms related to this study

Keywords

Other Study ID Numbers

  • FJUH115604

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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