Alvarez-Estevez Diego, Moret-Bonillo Vicente
Sleep Center, Medisch Centrum Haaglanden, 2512 VA The Hague, Netherlands.
Laboratory for Research and Development in Artificial Intelligence (LIDIA), Department of Computer Science, University of A Coruña, 15071 A Coruña, Spain.
Sleep Disord. 2015;2015:237878. doi: 10.1155/2015/237878. Epub 2015 Jul 21.
Automatic diagnosis of the Sleep Apnea-Hypopnea Syndrome (SAHS) has become an important area of research due to the growing interest in the field of sleep medicine and the costs associated with its manual diagnosis. The increment and heterogeneity of the different techniques, however, make it somewhat difficult to adequately follow the recent developments. A literature review within the area of computer-assisted diagnosis of SAHS has been performed comprising the last 15 years of research in the field. Screening approaches, methods for the detection and classification of respiratory events, comprehensive diagnostic systems, and an outline of current commercial approaches are reviewed. An overview of the different methods is presented together with validation analysis and critical discussion of the current state of the art.
由于睡眠医学领域的关注度不断提高以及手动诊断睡眠呼吸暂停低通气综合征(SAHS)的相关成本,SAHS的自动诊断已成为一个重要的研究领域。然而,不同技术的增加和异质性使得跟上最新发展有些困难。本文对SAHS计算机辅助诊断领域进行了文献综述,涵盖了该领域过去15年的研究。综述了筛查方法、呼吸事件检测和分类方法、综合诊断系统以及当前商业方法的概述。本文介绍了不同方法的概述,并对当前技术水平进行了验证分析和批判性讨论。