Integrating wearable data into circadian models
Integrating wearable data into circadian models
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DOI：
10.1016/j.coisb.2020.08.001
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发表时间：
2020-08-01
影响因子：
3.7
通讯作者：
Moreno, Jennette P.
中科院分区：
文献类型：
--
作者：
Hannay, Kevin M.;Moreno, Jennette P.
过去十年中可穿戴健康传感器的出现有可能彻底改变睡眠和昼夜节律的研究。特别是，最近取得了进展，在使用数学模型预测病人？使用可穿戴设备测量的数据来确定患者的内部昼夜节律状态。这是我们能够确定健康干预的最佳昼夜节律时间的重要一步。我们回顾了现有的数据拟合昼夜节律相位模型，重点是可穿戴数据集。最后，我们回顾了当前的建模范式，并探讨了在极限环振荡器模型中开发个性化参数集以进一步提高预测精度的途径。
The emergence of wearable health sensors in the last decade has the potential to revolutionize the study of sleep and circadian rhythms. In particular, recent progress has been made in the use of mathematical models in the prediction of a patient???s internal circadian state using data measured by wearable devices. This is a vital step in our ability to identify optimal circadian timing for health interventions. We review the available data for fitting circadian phase models with a focus on wearable data sets. Finally, we review the current modeling paradigms and explore avenues for developing personalized parameter sets in limit cycle oscillator models to further improve prediction accuracy.