用颗粒过器对自信意识的血压估计进行假设评分
IEEE journal of biomedical and health informatics
|June 26, 2023
概括
我们新的信任感知颗粒过器 (CAPF) 框架通过分析测量趋势和生理合理性来改善血压 (BP) 估计,排除错误的数据以获得准确的结果.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
- 生理监测 生理监测
背景情况:
- 精确的血压 (BP) 监测对于心血管健康管理至关重要.
- 现有的可穿戴BP监测技术在准确性和可靠性方面面临挑战.
- 积极的健康干预需要持续,可靠的BP趋势估计.
研究的目的:
- 引入和评估可信度感知颗粒过器 (CAPF) 框架,以提高BP估计.
- 评估CAPF提供稳定和准确的BP趋势估计的能力.
- 通过使用现实数据,对CAPF的绩效与既定标准进行验证.
主要方法:
- 在粒子过器 (序列蒙特卡洛) 框架内开发了一种新的信心意识机制.
- 根据测量协议和生理学可信度 (DBP/SBP对) 赋予BP状态假设的概率得分.
- 在生理压力测试期间使用生物阻抗 (Bio-Z) 可穿戴原型的数据评估CAPF.
主要成果:
- 与十种基线方法相比,CAPF在估计连续脉冲压 (PP),透气血压 (DBP) 和静脉血压 (SBP) 方面表现优异.
- 在超过3500个数据点中实现了高精度,PP的平均误差为-0.16 ± 3.75 mmHg,DBP的0.42 ± 4.39 mmHg,SBP的-0.09 ± 6.51 mmHg.
- CAPF的业绩符合AAMI和BHS标准,获得A级分类.
结论:
- CAPF框架为准确可靠的连续BP趋势估计提供了强大的解决方案.
- 信任意识机制有效过错误的测量,提高整体估计稳定性.
- 在可穿戴生理监测中,CAPF具有很大的应用潜力,特别是用于BP评估.
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