Current status and prospects of automatic sleep stages scoring: Review.

IF 3.2 4区 医学 Q2 ENGINEERING, BIOMEDICAL
Biomedical Engineering Letters Pub Date : 2023-07-10 eCollection Date: 2023-08-01 DOI:10.1007/s13534-023-00299-3
Maksym Gaiduk, Ángel Serrano Alarcón, Ralf Seepold, Natividad Martínez Madrid
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引用次数: 0

Abstract

The scoring of sleep stages is one of the essential tasks in sleep analysis. Since a manual procedure requires considerable human and financial resources, and incorporates some subjectivity, an automated approach could result in several advantages. There have been many developments in this area, and in order to provide a comprehensive overview, it is essential to review relevant recent works and summarise the characteristics of the approaches, which is the main aim of this article. To achieve it, we examined articles published between 2018 and 2022 that dealt with the automated scoring of sleep stages. In the final selection for in-depth analysis, 125 articles were included after reviewing a total of 515 publications. The results revealed that automatic scoring demonstrates good quality (with Cohen's kappa up to over 0.80 and accuracy up to over 90%) in analysing EEG/EEG + EOG + EMG signals. At the same time, it should be noted that there has been no breakthrough in the quality of results using these signals in recent years. Systems involving other signals that could potentially be acquired more conveniently for the user (e.g. respiratory, cardiac or movement signals) remain more challenging in the implementation with a high level of reliability but have considerable innovation capability. In general, automatic sleep stage scoring has excellent potential to assist medical professionals while providing an objective assessment.

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自动睡眠阶段评分的现状和前景:综述。
睡眠阶段的评分是睡眠分析的重要任务之一。由于手动程序需要大量的人力和财力资源,并且包含一些主观性,因此自动化方法可能会带来几个优势。这一领域有许多发展,为了提供全面的概述,有必要回顾最近的相关工作并总结方法的特点,这是本文的主要目的。为了实现这一目标,我们研究了2018年至2022年间发表的关于睡眠阶段自动评分的文章。在进行深入分析的最终选择中,在审查了总共515篇出版物后,纳入了125篇文章。结果显示,在分析EEG/EEG时,自动评分显示出良好的质量(Cohen’s kappa高达0.80以上,准确率高达90%以上) + EOG + EMG信号。同时,应该注意的是,近年来使用这些信号的结果质量没有突破。涉及可能对用户更方便地获取的其他信号(例如呼吸、心脏或运动信号)的系统在具有高可靠性但具有相当大的创新能力的实现中仍然更具挑战性。一般来说,自动睡眠阶段评分在提供客观评估的同时,对医疗专业人员有很好的帮助潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biomedical Engineering Letters
Biomedical Engineering Letters ENGINEERING, BIOMEDICAL-
CiteScore
6.80
自引率
0.00%
发文量
34
期刊介绍: Biomedical Engineering Letters (BMEL) aims to present the innovative experimental science and technological development in the biomedical field as well as clinical application of new development. The article must contain original biomedical engineering content, defined as development, theoretical analysis, and evaluation/validation of a new technique. BMEL publishes the following types of papers: original articles, review articles, editorials, and letters to the editor. All the papers are reviewed in single-blind fashion.
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