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Estimation of the sleep stages by the non-restrictive air mattress sensor - relation between the change in the heart rate and sleep stages

机译:通过非限制性气垫传感器估算睡眠阶段-心率变化与睡眠阶段之间的关系

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The health condition could be determined by how deeply he or she sleep every night. Thus every one would like to monitor his sleep characteristics. But it is not popular. The expensiveness and the strong physical and mental monitoring stress by the conventional Rechtschaffen & Kales method using a polygraph prevent it to be popular. Development of sleep quality monitoring methods easy, kind and convenient to people is required. The author presented an air mattress method to measure the human bio-information by a non-restrictive manner easy and kind to patients. If we can find some quantitative relations between the bio-information acquired by the air mattress sensor and the sleep stages judged from the polygraph data, the quality of sleep can be estimated easily and kindly. In this study, we investigated the relations in the low (circadian), middle (ultradian) and high frequency ranges, respectively and found the following relations; [low frequency] The gradient of sleep stages is strongly co-related with that of heart rate. [middle frequency] The sleep stages and the heart rate have the strong co-relation. [high frequency] The Non-REM oscillation can be estimated from the heart rate fluctuation. From these results, we built a simple mathematical model from which the sleep stages can be estimated only by the heart rate data acquired from the air mattress sensor.
机译:健康状况取决于他或她每晚睡多久。因此,每个人都想监视他的睡眠特征。但是它并不流行。传统的使用测谎仪的Rechtschaffen&Kales方法的昂贵性以及强大的身心监控压力使其无法普及。需要开发一种容易,友善和方便人们的睡眠质量监测方法。作者提出了一种气垫方法,以一种非限制性的方式对患者简便且友好地测量人体生物信息。如果我们可以找到充气床垫传感器获取的生物信息与根据测谎仪数据判断的睡眠阶段之间的定量关系,则可以轻松,友好地估算睡眠质量。在这项研究中,我们分别研究了低频(昼夜),中频(超音)和高频范围的关系,发现以下关系: [低频]睡眠阶段的梯度与心率密切相关。 [中频]睡眠阶段和心率之间有着很强的相关性。 [高频率]可以根据心率波动来估计Non-REM振荡。根据这些结果,我们建立了一个简单的数学模型,仅可以通过从充气床垫传感器获取的心率数据来估计睡眠阶段。

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