An E-health solution for automatic sleep classification according to Rechtschaffen and Kales:: Validation study of the Somnolyzer 24 x 7 utilizing the Siesta database
An E-health solution for automatic sleep classification according to Rechtschaffen and Kales:: Validation study of the Somnolyzer 24 x 7 utilizing the Siesta database
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DOI：
10.1159/000085205
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发表时间：
2005-01-01
影响因子：
3.2
通讯作者：
Dorffner, G
中科院分区：
文献类型：
--
作者：
Anderer, P;Gruber, G;Dorffner, G
迄今为止，世界范围内唯一接受的睡眠脑电图记录分类标准是 Rechtschaffen 和 Kales 于 1968 年发布的规则。尽管已经进行了多次尝试来实现分类过程的自动化，但迄今为止还没有发表任何方法在包括足够多的对照组和所有成人年龄范围的患者的研究中证明其有效性。本文描述了一种基于一个中央脑电图通道、两个眼电图通道和一个下巴肌电图通道的自动分类系统的开发和优化。它尽可能严格地遵守视觉评分的决策规则，并包括由人类专家执行的结构化质量控制程序。最终系统 (Somnolyzer 24 x 7(TM)) 包括原始数据质量检查、特征提取算法（睡眠/觉醒相关模式的密度和强度，例如睡眠纺锤波、δ波、SEM 和 REM）、特征矩阵合理性检查、设计为专家系统的分类器、用于 REM 阶段开始和结束的基于规则的平滑程序，最后是与年龄和性别匹配的正常健康对照（Siesta）的统计比较现场报告（TM））。专家系统根据先前的睡眠阶段、运动唤醒的发生以及 NREM/REM 睡眠周期内的时期位置来考虑阶段变化的不同先验概率。此外，将使用和不使用下巴 EMG 信号获得的结果相结合。 Siesta 多导睡眠图数据库（20-95 岁正常健康受试者和患有器质性或非器质性睡眠障碍的患者的 590 条记录）分为两半，分别随机分配给训练集和验证集。最终验证显示，Somnolyzer 24 x 7 与人类专家评分之间的总体逐个时期一致性为 80%（科恩 kappa：0.72），而对同一数据集评分的两位人类专家之间的评分者间可靠性为 77%（科恩 kappa：0.68）。两项 Somnolyzer 24 x 7 分析（包括由两名人类专家进行的结构化质量控制）显示，评估者间的可靠性接近 1（Cohen 的 kappa：0.991），这证实了质量控制程序引起的变异性，即大约 1% 的时期（在 9.5% 的记录中）发生变化，绝对可以忽略不计。因此，验证研究证明了Somnolyzer 24 x 7的高可靠性和有效性，并证明了其在临床常规和睡眠研究中的适用性。版权所有 (C) 2005 S. Karger AG，巴塞尔。
To date, the only standard for the classification of sleep-EEG recordings that has found worldwide acceptance are the rules published in 1968 by Rechtschaffen and Kales. Even though several attempts have been made to automate the classification process, so far no method has been published that has proven its validity in a study including a sufficiently large number of controls and patients of all adult age ranges. The present paper describes the development and optimization of an automatic classification system that is based on one central EEG channel, two EOG channels and one chin EMG channel. It adheres to the decision rules for visual scoring as closely as possible and includes a structured quality control procedure by a human expert. The final system (Somnolyzer 24 x 7(TM)) consists of a raw data quality check, a feature extraction algorithm ( density and intensity of sleep/wake-related patterns such as sleep spindles, delta waves, SEMs and REMs), a feature matrix plausibility check, a classifier designed as an expert system, a rule-based smoothing procedure for the start and the end of stages REM, and finally a statistical comparison to age- and sex-matched normal healthy controls (Siesta Spot Report(TM)). The expert system considers different prior probabilities of stage changes depending on the preceding sleep stage, the occurrence of a movement arousal and the position of the epoch within the NREM/REM sleep cycles. Moreover, results obtained with and without using the chin EMG signal are combined. The Siesta polysomnographic database (590 recordings in both normal healthy subjects aged 20-95 years and patients suffering from organic or nonorganic sleep disorders) was split into two halves, which were randomly assigned to a training and a validation set, respectively. The final validation revealed an overall epoch-by-epoch agreement of 80% (Cohen's kappa: 0.72) between the Somnolyzer 24 x 7 and the human expert scoring, as compared with an inter-rater reliability of 77% (Cohen's kappa: 0.68) between two human experts scoring the same dataset. Two Somnolyzer 24 x 7 analyses ( including a structured quality control by two human experts) revealed an inter-rater reliability close to 1 (Cohen's kappa: 0.991), which confirmed that the variability induced by the quality control procedure, whereby approximately 1% of the epochs (in 9.5% of the recordings) are changed, can definitely be neglected. Thus, the validation study proved the high reliability and validity of the Somnolyzer 24 x 7 and demonstrated its applicability in clinical routine and sleep studies. Copyright (C) 2005 S. Karger AG, Basel.