改进了使用不确定性测量和加权特征决策的信任区间估计,用于不使用袖口的血压测量
Soojeong Lee1, Mugahed A Al-Antari2, Gyanendra Prasad Joshi3
1Department of Computer Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Republic of Korea.
Bioengineering (Basel, Switzerland)
|February 26, 2025
概括
这项研究通过改善信心区间 (CI) 估计来增强无袖血压 (BP) 监测. 使用个人不确定性和加权特征的新方法提供了更准确和可靠的BP测量.
科学领域:
- 生物医学工程 生物医学工程
- 医疗器械 医疗器械
- 医疗信息学 医疗信息学
背景情况:
- 无袖式血压 (BP) 监测为传统方法提供了一种方便的替代方案.
- 现有的没有袖口的血压估计方法往往产生广泛的置信区间 (CI),限制了它们的临床实用性.
- 准确可靠的BP估计需要强大的不确定性量化和特征选择.
研究的目的:
- 开发一种改进的方法来估计无袖血压 (BP) 的置信区间 (CI).
- 通过使用个人不确定性指标和加权特征决定,提高无袖式BP估计的准确性和可靠性.
- 通过对现有的无袖血压监测技术来验证拟议的方法.
主要方法:
- 使用高斯过程回归 (GPR) 来获得BP估计的不确定性指标.
- 引导和不确定性方法被应用到GPR衍生的无袖BP估计,以改进个人CI估计.
- 使用加权特征决策,结合GPR和梯度增强算法 (GBA),用于识别对BP估计具有高度影响力的特征.
主要成果:
- 拟议的方法显示,缩血压 (SBP) 的平均误差标准偏差为2.94 mmHg,缩血压 (DBP) 的标准偏差为1.50 mmHg.
- 用GPR和GBA进行加权特征确定,SBP和DBP的平均绝对误差分别为1.46 mmHg和0.69 mmHg.
- 几乎所有受试者测试样本的血压估计都在计算的置信区间内,这表明其可靠性很高.
结论:
- 开发的方法显著改善了无袖血压监测的CI估计.
- 使用GBA将GPR与加权特征决策相结合,可以提高无袖式BP估计的准确性和可靠性.
- 这些发现表明,在非侵入性,连续血压监测技术方面有前途的进步.
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