Laboratory of Medical Physics, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Laboratory of Medical Physics, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece; Greek Aerospace Medical Association and Space Research (GASMA-SR), Thessaloniki, Greece.
Sleep Med Rev. 2021 Feb;55:101377. doi: 10.1016/j.smrv.2020.101377. Epub 2020 Sep 9.
Sleep staging is a vital process conducted in order to analyze polysomnographic data. To facilitate prompt interpretation of these recordings, many automatic sleep staging methods have been proposed. These methods rely on bio-signal recordings, which include electroencephalography, electrocardiography, electromyography, electrooculography, respiratory, pulse oximetry and others. However, advanced, uncomplicated and swift sleep-staging-evaluation is still needed in order to improve the existing polysomnographic data interpretation. The present review focuses on automatic sleep staging methods through bio-signal recording including current and future challenges.
睡眠分期是分析多导睡眠图数据的重要过程。为了方便这些记录的快速解读，已经提出了许多自动睡眠分期方法。这些方法依赖于生物信号记录，包括脑电图、心电图、肌电图、眼电图、呼吸、脉搏血氧饱和度等。然而，仍然需要先进、简单和快速的睡眠分期评估，以改善现有的多导睡眠图数据解读。本综述重点介绍了通过生物信号记录进行自动睡眠分期的方法，包括当前和未来的挑战。
