Study of continuous blood pressure estimation based on pulse transit time, heart rate and photoplethysmography-derived hemodynamic covariates
Study of continuous blood pressure estimation based on pulse transit time, heart rate and photoplethysmography-derived hemodynamic covariates
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DOI：
10.1007/s13246-018-0637-8
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发表时间：
2018-06-01
影响因子：
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通讯作者：
Ye, Xuesong
中科院分区：
文献类型：
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作者：
Feng, Jingjie;Huang, Zhongyi;Ye, Xuesong
人们普遍认为，脉搏传递时间（PTT）可以在短时间内跟踪血压（BP），而心率、僵硬指数等血流动力学协变量也可能有助于BP监测。本文推导了血压与pt -2之间的比例关系，并提出了一种改进的方法，在PTT的基础上采用血流动力学协变量进行连续血压估计。我们将重症监护多参数智能监测数据库中的28名受试者分为两组（有/没有心血管疾病），并利用基于正则化线性回归（RLR）的机器学习策略构建相应组不同协变量的BP模型。对个体进行RLR初始标定，再标定采用递归最小二乘算法。结果表明，当校准间隔延长到1200次心跳周期时，我们的方法的血压估计误差保持在医疗器械进步协会的限制范围内（- 0.98 +/- 6.00 mmHg @收缩压，0.02 +/- 4.98 mmHg @ DBP）。与其他两项代表性研究相比，Chen的方法在使用400次心跳校准间隔时保持准确（0.32 +/- 6.74 mmHg @ SBP, 0.94 +/- 5.37 mmHg @ DBP），而Poon的方法在使用200次心跳校准间隔时失败（- 1.97 +/- 10.59 mmHg @ SBP, 0.70 +/- 4.10 mmHg @ DBP）。通过使用额外的血流动力学协变量，我们的方法提高了基于ptt的血压估计的准确性，降低了校准频率，并且有可能更好地进行连续血压估计。
It is widely recognized that pulse transit time (PTT) can track blood pressure (BP) over short periods of time, and hemodynamic covariates such as heart rate, stiffness index may also contribute to BP monitoring. In this paper, we derived a proportional relationship between BP and PPT-2 and proposed an improved method adopting hemodynamic covariates in addition to PTT for continuous BP estimation. We divided 28 subjects from the Multi-parameter Intelligent Monitoring for Intensive Care database into two groups (with/without cardiovascular diseases) and utilized a machine learning strategy based on regularized linear regression (RLR) to construct BP models with different covariates for corresponding groups. RLR was performed for individuals as the initial calibration, while recursive least square algorithm was employed for the re-calibration. The results showed that errors of BP estimation by our method stayed within the Association of Advancement of Medical Instrumentation limits (- 0.98 +/- 6.00 mmHg @ SBP, 0.02 +/- 4.98 mmHg @ DBP) when the calibration interval extended to 1200-beat cardiac cycles. In comparison with other two representative studies, Chen's method kept accurate (0.32 +/- 6.74 mmHg @ SBP, 0.94 +/- 5.37 mmHg @ DBP) using a 400-beat calibration interval, while Poon's failed (- 1.97 +/- 10.59 mmHg @ SBP, 0.70 +/- 4.10 mmHg @ DBP) when using a 200-beat calibration interval. With additional hemodynamic covariates utilized, our method improved the accuracy of PTT-based BP estimation, decreased the calibration frequency and had the potential for better continuous BP estimation.