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Instantaneous monitoring of sleep fragmentation by point process heart rate variability and respiratory dynamics

机译:通过点过程心率变异性和呼吸动力学即时监测睡眠碎片

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摘要

We present a novel, automatic point-process approach that is able to provide continuous, instantaneous estimates of heart rate variability (HRV) and respiratory sinus arrhythmia (RSA) in long duration data recordings such as those during an entire night of sleep. We analyze subjects with and without sleep apnea who underwent diagnostic polysomnography. The proposed algorithm is able to quantify multi-scale high time resolution autonomic signatures of sleep fragmentation, such as arousals and stage transitions, throughout an entire night. Results demonstrate the ability of our methods to track fast dynamic transitions from sleep to wake and between REM sleep and other sleep stages, providing resolution details not available in sleep scoring summaries. An automatic threshold-based procedure is further able to detect brief arousals, with the instantaneous indices characterizing specific arousal dynamic signatures. © 2011 IEEE.
机译:我们提出了一种新颖的自动点处理方法,该方法能够在长时间的数据记录(例如在整个晚上的睡眠中)中提供心率变异性(HRV)和呼吸窦性心律不齐(RSA)的连续,瞬时估计。我们分析了接受诊断性多导睡眠图检查的有或没有睡眠呼吸暂停的受试者。所提出的算法能够量化整个晚上的睡眠碎片的多尺度高时间分辨率自主信号,例如唤醒和阶段转换。结果证明了我们的方法能够跟踪从睡眠到唤醒以及快速眼动睡眠和其他睡眠阶段之间的快速动态转变,提供了睡眠评分摘要中没有的解决方案详细信息。基于阈值的自动过程还能够检测短暂的唤醒,其中瞬时索引表征特定的唤醒动态签名。 ©2011 IEEE。

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