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首页> 外文期刊>Biosensors >Design and Evaluation of a Non-Contact Bed-Mounted Sensing Device for Automated In-Home Detection of Obstructive Sleep Apnea: A Pilot Study
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Design and Evaluation of a Non-Contact Bed-Mounted Sensing Device for Automated In-Home Detection of Obstructive Sleep Apnea: A Pilot Study

机译：无接触式床上休眠呼吸暂停自动检测的非接触式检测装置的设计与评价：试验研究

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We conducted a pilot study to evaluate the accuracy of a custom built non-contact pressure-sensitive device in diagnosing obstructive sleep apnea (OSA) severity as an alternative to in-laboratory polysomnography (PSG) and a Type 3 in-home sleep apnea test (HSAT). Fourteen patients completed PSG sleep studies for one night with simultaneous recording from our load-cell-based sensing device in the bed. Subjects subsequently installed pressure sensors in their bed at home and recorded signals for up to four nights. Machine learning models were optimized to classify sleep apnea severity using a standardized American Academy of Sleep Medicine (AASM) scoring of the gold standard studies as reference. On a per-night basis, our model reached a correct OSA detection rate of 82.9% (sensitivity = 88.9%, specificity = 76.5%), and OSA severity classification accuracy of 74.3% (61.5% and 81.8% correctly classified in-clinic and in-home tests, respectively). There was no difference in Apnea Hypopnea Index (AHI) estimation when subjects wore HSAT sensors versus load cells (LCs) only ( p -value = 0.62). Our in-home diagnostic system provides an unobtrusive method for detecting OSA with high sensitivity and may potentially be used for long-term monitoring of breathing during sleep. Further research is needed to address the lower specificity resulting from using the highest AHI from repeated samples.
机译：我们进行了一项试验研究，以评估定制的非接触式压敏装置的准确性在诊断阻塞性睡眠呼吸暂停（OSA）严重程度作为实验室多面程（PSG）的替代方案和家庭睡眠呼吸暂停测试的替代品（HSAT）。十四名患者完成了PSG睡眠研究，一天晚上，同时从床上的载荷电池的传感装置同时录制。受试者随后在家中安装压力传感器，并记录最多四个晚上的信号。机器学习模型经过优化，以使用标准化的美国睡眠学院（ASAM）作为参考的金标准研究的评分分类睡眠呼吸暂停严重性。在每晚，我们的模型达到了正确的OSA检出率为82.9％（灵敏度= 88.9％，特异性= 76.5％），OSA严重分类准确性为74.3％（61.5％和81.8％的诊所正确归类分别在家测试。当受试者佩戴HSAT传感器与称重传感器（LCS）相比（P -Value = 0.62）时，呼吸暂停次阅呼吸暂停次数（AHI）估计没有差异。我们的家庭诊断系统提供了一种不引人注意的方法，用于检测高灵敏度的OSA，可能用于睡眠期间呼吸的长期监测。需要进一步的研究来解决使用来自重复样品的最高AHI而导致的较低特异性。

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