标题： 睡眠中皮层觉醒的自动检测及其对日间嗜睡的贡献 显示英文标题

标题： Automatic Detection of Cortical Arousals in Sleep and their Contribution to Daytime Sleepiness

摘要： 皮层觉醒是睡眠中短暂的紊乱事件，可能自发发生或对如呼吸暂停事件等刺激作出反应。 在人类多导睡眠图记录（PSGs）中，觉醒检测的金标准是专家人工标注，这种方法存在显著的评分者间变异性。 在本研究中，我们开发了一种自动化方法，即多模态觉醒检测器（MAD），使用深度学习方法来检测觉醒。 MAD在2,889个PSGs上进行训练，以1秒为间隔检测皮层觉醒和清醒状态。 此外，在873名受试者的1447个MSLT实例中分析了PSGs上MAD预测标签与次日平均睡眠潜伏期（MSL）之间的关系，MSL是白天嗜睡程度的反映。 在一个包含1,026个PSGs的数据集中，MAD在觉醒检测中的F1得分为0.76，而清醒状态的预测准确率为0.95。 在60个由多位人类专家技术人员评分的PSGs中，MAD在觉醒检测中的表现显著优于平均人类评分者，F1得分差异为0.09。 在控制其他已知协变量后，觉醒指数翻倍与MSL平均减少40秒相关（$\beta$= -0.67，p = 0.0075）。 MAD的表现优于平均人类专家，且MAD预测的觉醒被证明是MSL的重要预测因子，这表明MAD具有临床有效性。 显示英文摘要

摘要： Cortical arousals are transient events of disturbed sleep that occur spontaneously or in response to stimuli such as apneic events. The gold standard for arousal detection in human polysomnographic recordings (PSGs) is manual annotation by expert human scorers, a method with significant interscorer variability. In this study, we developed an automated method, the Multimodal Arousal Detector (MAD), to detect arousals using deep learning methods. The MAD was trained on 2,889 PSGs to detect both cortical arousals and wakefulness in 1 second intervals. Furthermore, the relationship between MAD-predicted labels on PSGs and next day mean sleep latency (MSL) on a multiple sleep latency test (MSLT), a reflection of daytime sleepiness, was analyzed in 1447 MSLT instances in 873 subjects. In a dataset of 1,026 PSGs, the MAD achieved a F1 score of 0.76 for arousal detection, while wakefulness was predicted with an accuracy of 0.95. In 60 PSGs scored by multiple human expert technicians, the MAD significantly outperformed the average human scorer for arousal detection with a difference in F1 score of 0.09. After controlling for other known covariates, a doubling of the arousal index was associated with an average decrease in MSL of 40 seconds ($\beta$ = -0.67, p = 0.0075). The MAD outperformed the average human expert and the MAD-predicted arousals were shown to be significant predictors of MSL, which demonstrate clinical validity the MAD.