Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
NA
107 participants
INTERVENTIONAL
2022-10-19
2025-07-11
Brief Summary
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Detailed Description
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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
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Study Design
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NA
SINGLE_GROUP
DIAGNOSTIC
NONE
Study Groups
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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.
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
Interventions
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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
Eligibility Criteria
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Inclusion 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
* 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)
19 Years
FEMALE
Yes
Sponsors
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Gangnam Severance Hospital
OTHER
Sky Labs
INDUSTRY
Responsible Party
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Principal Investigators
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Won Joo Kim, MD, PhD
Role: PRINCIPAL_INVESTIGATOR
Gangnam Severance Hospital
Locations
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Gangnam Severance Hospital
Seoul, , South Korea
Countries
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Central Contacts
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Facility Contacts
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References
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Peppard PE, Young T, Palta M, Skatrud J. Prospective study of the association between sleep-disordered breathing and hypertension. N Engl J Med. 2000 May 11;342(19):1378-84. doi: 10.1056/NEJM200005113421901.
Arzt M, Young T, Finn L, Skatrud JB, Bradley TD. Association of sleep-disordered breathing and the occurrence of stroke. Am J Respir Crit Care Med. 2005 Dec 1;172(11):1447-51. doi: 10.1164/rccm.200505-702OC. Epub 2005 Sep 1.
Doherty LS, Kiely JL, Swan V, McNicholas WT. Long-term effects of nasal continuous positive airway pressure therapy on cardiovascular outcomes in sleep apnea syndrome. Chest. 2005 Jun;127(6):2076-84. doi: 10.1378/chest.127.6.2076.
Kim J, In K, Kim J, You S, Kang K, Shim J, Lee S, Lee J, Lee S, Park C, Shin C. Prevalence of sleep-disordered breathing in middle-aged Korean men and women. Am J Respir Crit Care Med. 2004 Nov 15;170(10):1108-13. doi: 10.1164/rccm.200404-519OC. Epub 2004 Sep 3.
Other Identifiers
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3-2022-0207
Identifier Type: -
Identifier Source: org_study_id
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