Year: 2024
Type: conference-paper
Abstract: Sleep apnea syndrome (SAS) is a common but serious sleep disorder affecting millions worldwide.It is marked by pauses in breathing over 10 seconds (apnea) or shallow breathing (hypopnea) during sleep, disrupting the sleep cycle and causing fatigue.Untreated SAS increases the risk of stroke, heart disease, high blood pressure, and mental health issues like depression and anxiety.Despite being treatable, many cases remain undiagnosed due to symptoms being misattributed or the inaccessibility of polysomnography (PSG), the diagnostic gold standard.Recently, more accessible methods like electrocardiography or photoplethysmography (PPG) have shown promise, especially with wearable devices.Our work explores using single-channel PPG and deep learning methods (AlexNet, custom CNN, ZF-net) to classify SAS using data from the Multi-Ethnic Study of Atherosclerosis.Using all-night data from 120 patients with the highest apneahypopnea index, we trained on around 9,000 non-apneic and 9,000 SAS-positive intervals, achieving 87.7% accuracy and 85.1% sensitivity, showing the potential for early diagnosis without PSG.
Source: Computing in cardiology
Authors: Martin Kralik, Andrea Nemcova, Jiri Kozumplik, Eniko Vargova
Institution: Brno University of Technology
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
Awards: G1261793039, G1276754516, G1294553593, G1640378483, G1983464145, G2095942735, G2144938473, G22458031, G2726417417, G2837638605, G2862297731, G290884426, G291913881, G3093995152, G3595232572, G370977179, G3955673373, G3990748671, G4249524944, G4309390892, G4590187187, G4986157935, G5075046117, G5108002584, G5653954166, G5654179670, Institute for Clinical and Translational Research, G66341962, G6742279884, G6856766826, G7166352866, G7511203839, G78770644, Clinical and Translational Science Award, G8145863542, G8852914737, G9000004549, G9000004784, G9000006353, G9000017360, G9000019818, G9000025517, G9000038858, G9000063950, G9000065698, G9000068995, G9000347892, G91634571, G94668252, G991334795
OpenAlex ID: W4405435119