Obstructive sleep apnea screening by heart rate variability-based apnea/normal respiration discriminant model
Obstructive sleep apnea screening by heart rate variability-based apnea/normal respiration discriminant model
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DOI：
10.1088/1361-6579/ab57be
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发表时间：
2019-12-01
影响因子：
3.2
通讯作者：
Kadotani, Hiroshi
中科院分区：
文献类型：
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作者：
Nakayama, Chikao;Fujiwara, Koichi;Kadotani, Hiroshi
目的：阻塞性睡眠呼吸暂停(OSA)是一种常见的睡眠障碍，但由于患者在日常生活中很难注意到OSA，大多数患者没有得到诊断和治疗。多导睡眠图(PSG)是诊断睡眠障碍的金标准测试，但许多医院无法进行。这一事实促使我们开发一种简单的在家筛查OSA的系统。方法：呼吸暂停时自主神经系统发生变化，这种变化会影响心率变异性(HRV)。本工作基于心率变异性分析和机器学习技术开发了一种新的呼吸暂停筛查方法。建立呼吸暂停/正常呼吸(A/N)判别模型，用于每一次心率测量的呼吸状态估计，并引入呼吸暂停/睡眠比率作为最终诊断。采用随机森林建立A/N判别模型，并用PhysioNet呼吸暂停心电数据库进行训练。主要结果：将该方法应用于临床PSG数据，对该方法的筛选性能进行了评估。灵敏度和特异度分别达到76%和92%，可与现有睡眠实验室使用的便携式睡眠监测设备相媲美。意义：由于建议的OSA筛查方法比现有设备更容易使用，它将有助于OSA的治疗。
Objective: Obstructive sleep apnea (OSA) is a common sleep disorder; however, most patients are undiagnosed and untreated because it is difficult for patients themselves to notice OSA in daily living. Polysomnography (PSG), which is the gold standard test for sleep disorder diagnosis, cannot be performed in many hospitals. This fact motivates us to develop a simple system for screening OSA at home. Approach: The autonomic nervous system changes during apnea, and such changes affect heart rate variability (HRV). This work develops a new apnea screening method based on HRV analysis and machine learning technologies. An apnea/normal respiration (A/N) discriminant model is built for respiration condition estimation for every heart rate measurement, and an apnea/sleep ratio is introduced for final diagnosis. A random forest is adopted for the A/N discriminant model construction, which is trained with the PhysioNet apnea-ECG database. Main results: The screening performance of the proposed method was evaluated by applying it to clinical PSG data. Sensitivity and specificity achieved 76% and 92%, respectively, which are comparable to existing portable sleep monitoring devices used in sleep laboratories. Significance: Since the proposed OSA screening method can be used more easily than existing devices, it will contribute to OSA treatment.