Updating Deep Learning Algorithms for OSA Monitoring

July 22, 2024 updated by: Sky Labs

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

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.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

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.

Study Type

Interventional

Enrollment (Estimated)

107

Phase

  • Not Applicable

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 Contact Backup

Study Locations

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

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

Patients scheduled for Level 1 polysomnography at a sleep center who meet all of the following criteria:

  • Aged 19 years or older
  • Have listened to and understood a thorough explanation of the clinical study and voluntarily agreed to participate

Exclusion Criteria:

  • Under 19 years of age
  • Unable to collect normal signals during the pre-test or wearing of the CART-I PLUS device
  • Refuse to participate in the clinical study
  • Have cognitive impairments to the extent that they cannot understand the explanation of the clinical study and therefore cannot make a voluntary decision to participate (e.g., legally incompetent individuals)

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

  • Primary Purpose: Diagnostic
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Level 1 polysomnography patient
For patients undergoing Level 1 polysomnography, simultaneous collection of photoplethysmography (PPG) signals and polysomnography data is performed using the CART-I PLUS device.
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

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Accuracy of the algorithm and the 95% confidence interval
Time Frame: 11 hours
Present the accuracy of the algorithm and the 95% confidence interval. If the lower bound of the 95% confidence interval exceeds a minimum accuracy of 0.85, it is considered clinically significant.
11 hours

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Accuracy and 95% confidence intervals for each interval
Time Frame: 11 hours
Present the accuracy and 95% confidence intervals for each interval. Additionally, precision, recall, ROC curve, and AUC may be presented. The performance comparison between algorithms will use the bootstrap method, and a p-value less than 0.05 will be considered statistically significant.
11 hours

Collaborators and Investigators

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

Sponsor

Sky Labs

Collaborators

Gangnam Severance Hospital

Investigators

  • Principal Investigator: Won Joo Kim, MD, PhD, Gangnam Severance Hospital

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

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 (Actual)

October 19, 2022

Primary Completion (Estimated)

April 22, 2025

Study Completion (Estimated)

July 11, 2025

Study Registration Dates

First Submitted

July 22, 2024

First Submitted That Met QC Criteria

July 22, 2024

First Posted (Actual)

July 26, 2024

Study Record Updates

Last Update Posted (Actual)

July 26, 2024

Last Update Submitted That Met QC Criteria

July 22, 2024

Last Verified

July 1, 2024

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 3-2022-0207

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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