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Updating Deep Learning Algorithms for OSA Monitoring

NCT06522815 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 107

Last updated 2024-07-26

No results posted yet for this study

Summary

The objective is to enhance the reliability of the algorithm to match that of Level 1 polysomnography by leveraging the diverse data obtained from Level 1 polysomnography to refine the deep learning algorithm.

Conditions

Interventions

DEVICE

CART-I plus

CART-I PLUS collects signals in two ways: ECG: Utilizes the metal on the inner and outer sides as electrodes to detect subtle electrical changes resulting from the contraction and relaxation of the heart muscle. PPG: Emits LED light into the blood vessels inside the finger and collects the signal reflected by the blood flow, thereby gathering data on the pulse and functional oxygen saturation (SpO2) of arterial hemoglobin. In this clinical trial, PPG signals will be continuously collected during the polysomnography using the PPG method.

DEVICE

Polysomnography

In polysomnography, the following data are collected: Electrocardiogram (ECG), Electroencephalogram (EEG), Electromyogram (EMG), Electrooculogram (EOG), Oxygen Saturation (SpO2) Respiratory Analysis, Body Position Monitoring

Sponsors & Collaborators

  • Gangnam Severance Hospital

    collaborator OTHER

  • Sky Labs

    lead INDUSTRY

Principal Investigators

  • Won Joo Kim, MD, PhD · Gangnam Severance Hospital

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
19 Years
Sex
FEMALE
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-10-19
Primary Completion
2025-04-22
Completion
2025-07-11

Countries

  • South Korea

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06522815 on ClinicalTrials.gov