NCT06522815

Updating Deep Learning Algorithms for OSA Monitoring

Deep Learning Algorithm Update Using Real Patients for Out-of-hospital Obstructive Sleep Apnea Monitoring

• Status: Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 107 (estimated)
• Sponsor: Sky Labs · Industry
• Sex: Female
• Age: 19 Years
• Healthy volunteers: Accepted

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.

Detailed description

Patients undergoing Level 1 polysomnography are equipped with the CART-I PLUS device, for collecting polysomnography data alongside concurrent photoplethysmography (PPG) signals. The collected data is categorized into apnea, hypopnea, and normal segments based on the polysomnography results. Utilizing the PPG and accelerometer (ACC) signals from the CART-I PLUS, metrics such as SaO2 (oxygen saturation), respiratory rate, heart rate (HR), heart rate variability (HRV), and body movement are calculated for each segment. These metrics, along with the PPG and ACC signals, are then used to develop a deep learning model that classifies the segments into apnea, hypopnea, or normal. Participants are divided into training and validation sets. The deep learning model is trained on data from the participants in the training set, and its performance is evaluated using the validation set. The algorithm is constructed using convolutional neural networks (CNN), recurrent neural networks (RNN), attention mechanisms, and other advanced techniques recognized for their efficacy in classification tasks, specifically for identifying apnea, hypopnea, and normal segments.

Conditions

• Obstructive Sleep Apnea
• Obstructive Sleep Apnea-hypopnea

Interventions

Type	Name	Description
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

Timeline

• Start date: 2022-10-19
• Primary completion: 2025-04-22
• Completion: 2025-07-11
• First posted: 2024-07-26
• Last updated: 2024-07-26

Locations

1 site across 1 country: South Korea