Predicting vigilance impairment in high-risk shift work occupations is critical to help to reduce workplace errors and accidents. Current methods rely on multi-night, often manually entered, sleep data. This study developed a machine learning model f...
IEEE journal of biomedical and health informatics
Jan 4, 2024
Despite the recent advances in automatic sleep staging, few studies have focused on real-time sleep staging to promote the regulation of sleep or the intervention of sleep disorders. In this paper, a novel network named SwSleepNet, that can handle bo...
Sleep spindles (SSs) and K-complexes (KCs) are brain patterns involved in cognitive functions that appear during sleep. Large-scale sleep studies would benefit from precise and robust automatic sleep event detectors, capable of adapting the variabili...
BACKGROUND: Sleep and physical activity suggestions for panic disorder (PD) are critical but less surveyed. This two-year prospective cohort study aims to predict panic attacks (PA), state anxiety (SA), trait anxiety (TA) and panic disorder severity ...
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Dec 20, 2023
PURPOSE: To conduct a comparative performance evaluation of GPT-3.5, GPT-4 and Google Bard in self-assessment questions at the level of the American Sleep Medicine Certification Board Exam.
IEEE journal of biomedical and health informatics
Nov 7, 2023
Obstructive sleep apnea (OSA) is a sleep disorder that causes partial or complete cessation of breathing during an individual's sleep. Various methods have been proposed to automatically detect OSA events, but little work has focused on predicting su...
IEEE journal of biomedical and health informatics
Nov 7, 2023
Automatic sleep staging has been an active field of development. Despite multiple efforts, the area remains a focus of research interest. Indeed, while promising results have reported in past literature, uptake of automatic sleep scoring in the clini...
Deep learning methods have gained significant attention in sleep science. This study aimed to assess the performance of a deep learning-based sleep stage classification model constructed using fewer physiological parameters derived from cardiorespira...
Given the significant impact of sleep on overall health, radar technology offers a promising, non-invasive, and cost-effective avenue for the early detection of sleep disorders, even prior to relying on polysomnography (PSG)-based classification. In ...
OBJECTIVE: To investigate individual effects of a three-week sleep robot intervention in adults with ADHD and insomnia, and to explore participants' experiences with the intervention.