The identification of sleep stages is essential in the diagnostics disorders, among which obstructive apnea (OSA) one most prevalent. However, manual scoring time-consuming, subjective, and costly. To overcome this shortcoming, we aimed to develop an accurate deep learning approach for automatic classification study effect OSA severity on accuracy. Overnight polysomnographic recordings from a public dataset healthy individuals (Sleep-EDF, n = 153) clinical (n 891) patients with suspected...

The aim was to investigate how the severity of apneas, hypopneas, and related desaturations is associated with obstructive sleep apnea (OSA)-related daytime sleepiness.Multiple Sleep Latency Tests polysomnographic recordings 362 patients OSA were retrospectively analyzed novel diagnostic parameters (eg, obstruction desaturation severity), incorporating desaturations, computed. Conventional statistical analysis multivariate analyses utilized connection apnea-hypopnea index (AHI), oxygen...

Accurate identification of sleep stages is essential in the diagnosis disorders (e.g. obstructive apnea [OSA]) but relies on labor-intensive electroencephalogram (EEG)-based manual scoring. Furthermore, long-term assessment actigraphy differentiating only between wake and periods without identifying specific having low reliability after onset. To address these issues, we aimed to develop an automatic method for from photoplethysmogram (PPG) signal obtained with a simple finger pulse...

In response to the growing clinico-economic need for comprehensive home-based sleep testing, we recently developed a self-applicable facial electrode set with screen-printed Ag/AgCl electrodes. Our previous studies revealed that nocturnal sweating is common problem, causing low-frequency artifacts in measured electroencephalography (EEG) signals. As designed be used without skin abrasion, not surprisingly this leads relatively high electrode-skin impedances, significant impedance changes due...

Current diagnostic parameters estimating obstructive sleep apnoea (OSA) severity have a poor connection to the psychomotor vigilance of OSA patients. Thus, we aimed investigate how apnoeas, hypopnoeas and intermittent hypoxaemia is associated with impaired vigilance.We retrospectively examined type I polysomnography data corresponding tasks (PVTs) 743 consecutive patients (apnoea-hypopnoea index (AHI) ≥5 events·h-1). Conventional (e.g. AHI oxygen desaturation (ODI)) novel obstruction...

Determining sleep stages accurately is an important part of the diagnostic process for numerous disorders. However, as stage scoring done manually following visual rules there can be considerable variation in staging between different scorers. Thus, this study aimed to comprehensively evaluate inter-rater agreement staging. A total 50 polysomnography recordings were scored by 10 independent scorers from seven centres. We used scorings calculate a majority score taking that was most each...

Abstract The severity of obstructive sleep apnea (OSA) is classified using apnea-hypopnea index (AHI). Accurate determination AHI currently requires manual analysis and complicated registration setup making it expensive labor intensive. Partially for these reasons, OSA a heavily underdiagnosed disease as only 7% women 18% men suffering from have diagnosis. To resolve issues, we introduce an artificial neural network (ANN) that estimates oxygen desaturation (ODI) the blood saturation signal...

The diagnosis of obstructive sleep apnea is based on daytime symptoms and the frequency respiratory events during night. are scored manually from polysomnographic recordings, which time-consuming expensive. Therefore, automatic scoring methods could considerably improve efficiency diagnostics release resources currently needed for manual to other areas medicine. In this study, we trained a long short-term memory neural network using input signals peripheral blood oxygen saturation,...

Abstract Study Objectives To assess the relationship between obstructive sleep apnea (OSA) severity and fragmentation, accurate differentiation wakefulness is needed. Sleep staging usually performed manually using electroencephalography (EEG). This time-consuming due to complexity of EEG setup amount work in manual scoring. In this study, we aimed develop an automated deep learning-based solution OSA-related fragmentation based on photoplethysmography (PPG) signal. Methods A combination...

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Objective:</i> Obstructive sleep apnea (OSA) is diagnosed using the apnea-hypopnea index (AHI), which average number of respiratory events per hour sleep. Recently, machine learning algorithms for automatic AHI assessment have been developed, but many them do not consider individual stages or events. In this study, we aimed to develop a deep model simultaneously score both and The hypothesis was...

The high number of fatal crashes caused by driver drowsiness highlights the need for developing reliable detection methods. An ideal system should estimate multiple levels accurately without intervening in driving task. This paper proposes a multi-level deep neural network-based classification using combination electrocardiogram and respiration signals. proposed method is based on convolutional networks (CNNs) long short-term memory (LSTM) classifying concurrently heart rate variability...

Obstructive sleep apnea (OSA) is associated with the progression of cardiovascular diseases, arrhythmias, and sudden cardiac death (SCD). However, acute impacts OSA its consequences on heart function are not yet fully elucidated. We hypothesized that desaturation events acutely destabilize ventricular repolarization, presence accompanying arousals magnifies this destabilization. Ventricular repolarization lability measures, comprising rate corrected QT (QTc), short-time-variability (STVQT),...

The traditional sleep staging involves manual scoring of electroencephalogram (EEG), electrooculogram (EOG), and electromyogram signals during polysomnography (PSG), which is laborious susceptible to human errors. Previous studies have explored several automated methods utilizing fewer EEG signals, for deep-learning shown promising results. Despite the availability various signal combinations in PSGs, performance different accurate not fully explored. We hypothesize that will yield...

Summary Polysomnography is the only internationally recognized method to diagnose paediatric obstructive sleep apnea, thus, simpler and more cost‐effective diagnostic tools are urgently needed. This study aimed validate manual scoring of frontal self‐applicable electroencephalography against polysomnography in a cohort. The were simultaneously recorded for 1 night ( n = 102) 10–13‐year‐old children. Scoring was performed according American Academy Sleep Medicine rules, with minor adjustments...

Adipocytokines are hormones regulating energy metabolism and appetite according to recent reports also inflammatory responses including ischaemia–reperfusion injury. Based on experimental data, we hypothesized that the levels of adipocytokines adiponectin, adipsin, leptin and/or resistin would correlate with myocardial injury, inflammation oxidative stress during cardiac surgery. Thirty-two patients undergoing an elective on-pump coronary artery bypass graft surgery (CABG) cardiopulmonary...

Positional obstructive sleep apnea (OSA) is common among OSA patients. In severe OSA, the obstruction events are longer in supine compared to nonsupine positions. Corresponding scientific information on mild and moderate lacking. We studied whether individual desaturation event severity increased position all categories of linked categories. Polygraphic recordings 2026 patients were retrospectively analyzed. The apnea, hypopnea durations depth, duration, area 526 included between positions...

Abstract Low long-term heart rate variability (HRV), often observed in obstructive sleep apnea (OSA) patients, is a known risk factor for cardiovascular diseases. However, it unclear how the type or duration of individual respiratory events modulate ultra-short-term HRV and beat-to-beat intervals (RR intervals). We aimed to examine sex-specific changes RR interval during after apneas hypopneas various durations. Electrocardiography signals, recorded as part clinical polysomnography, 758...

Current diagnostics of sleep apnea relies on the time-consuming manual analysis complex registrations, which is impractical for routine screening in hospitalized patients with a high probability apnea, e.g. those experiencing acute stroke or transient ischemic attacks (TIA). To overcome this shortcoming, we aimed to develop convolutional neural network (CNN) capable estimating severity and TIA based solely nocturnal oxygen saturation (SpO2) signal. The CNN was trained SpO2 signals derived...

Reliable, automated, and user-friendly solutions for the identification of sleep stages in home environment are needed various clinical scientific research settings. Previously we have shown that signals recorded with an easily applicable textile electrode headband (FocusBand, T 2 Green Pty Ltd) contain characteristics similar to standard electrooculography (EOG, E1-M2). We hypothesize electroencephalographic (EEG) using enough EOG order develop automatic neural network-based staging method...