合规预测可以确定可穿戴的无袖血压的数量
Zhan Shen1, Tapabrata Chakraborti2,3, Christopher R S Banerji2,4
1School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China.
这项研究引入了使用可穿戴传感器无袖血压监测的新算法. 它提供可靠的24小时血压置信区间,增强对可穿戴健康技术的信任.
科学领域:
- 生物医学工程 生物医学工程
- 心血管技术的心血管技术
- 医疗信息学 医疗信息学
背景情况:
- 穿戴式无袖血压 (BP) 监测在准确性和可靠性方面面临挑战,特别是在门诊条件下.
- 现有的技术难以有效地跟踪动态BP变化,限制了它们的临床实用性.
- 需要使用可穿戴设备进行可靠的门诊血压估计.
研究的目的:
- 开发和验证一种用于24小时门诊无袖血压置信区间 (CI) 估计的算法.
- 通过可穿戴式心电图 (ECG) 和光电脑图 (PPG) 数据,确保真正的血压值的合规保证覆盖.
- 为了增强患者和医生对可穿戴血压监测设备的信任.
主要方法:
- 开发了一种基于量子损失的梯度增强回归树 (GBRT) 模型,以估计门诊血压并量化模型不确定性.
- 采用符合性预测来校准模型的不确定性,并生成具有保证覆盖的CI.
- 使用483名参与者在Aurora-BP研究数据集中的门诊生理数据验证了算法.
主要成果:
- 该算法提供了24小时的门诊血压估计与置信区间.
- 白天阶段:静脉血压 (SBP) 的平均绝对差异 (MAD) 为14.32 mmHg,静脉血压 (DBP) 的平均绝对差异为9.53 mmHg.
- 夜间阶段:SBP的MAD为14.22 mmHg,DBP的MAD为10.13 mmHg.
结论:
- 开发的算法提供可靠的24小时门诊无袖血压估计,保证覆盖范围.
- 合规预测的整合提高了可穿戴设备的BP读数的可靠性.
- 这项技术有可能在高血压预防,查和管理方面发挥重要作用.
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