Lambert Isabelle, Peter-Derex Laure
APHM, Timone Hospital, Sleep Unit, Epileptology and Cerebral Rhythmology, Marseille, France.
Aix Marseille University, INSERM, Institut de Neuroscience des Systemes, Marseille, France.
Nat Sci Sleep. 2023 Jun 29;15:479-490. doi: 10.2147/NSS.S401270. eCollection 2023.
The recommendations for identifying sleep stages based on the interpretation of electrophysiological signals (electroencephalography [EEG], electro-oculography [EOG], and electromyography [EMG]), derived from the Rechtschaffen and Kales manual, were published in 2007 at the initiative of the American Academy of Sleep Medicine, and regularly updated over years. They offer an important tool to assess objective markers in different types of sleep/wake subjective complaints. With the aims and advantages of simplicity, reproducibility and standardization of practices in research and, most of all, in sleep medicine, they have overall changed little in the way they describe sleep. However, our knowledge on sleep/wake physiology and sleep disorders has evolved since then. High-density electroencephalography and intracranial electroencephalography studies have highlighted local regulation of sleep mechanisms, with spatio-temporal heterogeneity in vigilance states. Progress in the understanding of sleep disorders has allowed the identification of electrophysiological biomarkers better correlated with clinical symptoms and outcomes than standard sleep parameters. Finally, the huge development of sleep medicine, with a demand for explorations far exceeding the supply, has led to the development of alternative studies, which can be carried out at home, based on a smaller number of electrophysiological signals and on their automatic analysis. In this perspective article, we aim to examine how our description of sleep has been constructed, has evolved, and may still be reshaped in the light of advances in knowledge of sleep physiology and the development of technical recording and analysis tools. After presenting the strengths and limitations of the classification of sleep stages, we propose to challenge the "EEG-EOG-EMG" paradigm by discussing the physiological signals required for sleep stages identification, provide an overview of new tools and automatic analysis methods and propose avenues for the development of new approaches to describe and understand sleep/wake states.
基于对电生理信号（脑电图[EEG]、眼电图[EOG]和肌电图[EMG]）解读来识别睡眠阶段的建议源自 Rechtschaffen 和 Kales 手册，于 2007 年在美国睡眠医学学会的倡议下发布，并多年来定期更新。它们为评估不同类型睡眠/觉醒主观主诉中的客观指标提供了重要工具。鉴于其在研究实践中，尤其是在睡眠医学中具有简单、可重复和标准化的目的及优势，它们在描述睡眠的方式上总体变化不大。然而，从那时起，我们对睡眠/觉醒生理学和睡眠障碍的认识有了发展。高密度脑电图和颅内脑电图研究突出了睡眠机制的局部调节，警觉状态存在时空异质性。对睡眠障碍理解的进展使得能够识别出比标准睡眠参数与临床症状和结果相关性更好的电生理生物标志物。最后，睡眠医学的巨大发展，其探索需求远远超过供给，导致了替代研究的发展，这些研究可以在家中基于较少数量的电生理信号及其自动分析来进行。在这篇观点文章中，我们旨在探讨我们对睡眠的描述是如何构建的、如何演变的，以及鉴于睡眠生理学知识的进步和技术记录与分析工具的发展，它可能仍如何被重塑。在介绍了睡眠阶段分类的优势和局限性之后，我们提议通过讨论识别睡眠阶段所需的生理信号来挑战“EEG - EOG - EMG”范式，概述新工具和自动分析方法，并提出开发描述和理解睡眠/觉醒状态新方法的途径。
