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Mahya Saffarpour¹, Debraj Basu¹, Fatemeh Radaei¹

¹Department of Electrical and Computer Engineering, UC Davis.

ACM transactions on computing for healthcare

|February 13, 2024

概括

在动脉血压 (ABP) 波形中,Physiowise (PW) 改进了双隙 (DN) 检测,特别是在老化或生病的血管中. 这种物理意识的方法提高了准确性,并减少了识别这一关键心血管指标的错误.

科学领域:

心血管生理学心血管生理学
生物医学工程生物医学工程
信号处理信号处理

背景情况:

动脉血压 (ABP) 波形中的二突 (DN) 对于评估心血管功能至关重要.
衰老和病理性血管硬性减少了DN的突出性,使自动识别复杂化.
由于噪音或血液动力学不稳定的ABP波形变形进一步挑战了DN检测.

研究的目的:

开发一种可靠和可通用的方法,用于自动识别双突.
为了提高在具有挑战性的ABP波形中DN检测的准确性,包括那些有变形的波形.
解决老化和病理条件下当前方法的局限性.

主要方法:

开发了一种以物理意识为基础的方法,Physiowise (PW).
该方法使用心血管模型来增强ABP波形,减少变形.
预定义的规则应用于用于DN定位的增强信号.
还提出了一种混合方法,允许用户定义规则.

主要成果:

在Physiowise (PW) 中,整体平均误差改善率为52%.
在关键的30ms误差范围内,检测精度增加了16%.
这种方法在血液和败血症下的猪的体内数据上得到了验证.

结论:

拟议的Physiowise (PW) 方法有效地增强了ABP波形中的二突识别.
这种方法提供了更好的准确性和稳定性,特别是在血管硬和波形变形的情况下.
混合选项提供了与现有或自定义检测算法集成的灵活性.

关键词:

迪克罗特的标记标识发生出血发生出血基于模型的方法基于模型的方法.基于规则的方法是基于规则的方法.败血症这是一种败血症.

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