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Updating Deep Learning Algorithms for OSA Monitoring
Sponsor: Sky Labs
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.
Official title: Deep Learning Algorithm Update Using Real Patients for Out-of-hospital Obstructive Sleep Apnea Monitoring
Key Details
Gender
FEMALE
Age Range
19 Years - Any
Study Type
INTERVENTIONAL
Enrollment
107
Start Date
2022-10-19
Completion Date
2025-07-11
Last Updated
2024-07-26
Healthy Volunteers
Yes
Interventions
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.
Polysomnography
In polysomnography, the following data are collected: Electrocardiogram (ECG), Electroencephalogram (EEG), Electromyogram (EMG), Electrooculogram (EOG), Oxygen Saturation (SpO2) Respiratory Analysis, Body Position Monitoring
Locations (1)
Gangnam Severance Hospital
Seoul, South Korea