Noninvasive cuffless blood pressure estimation using pulse transit time and Hilbert-Huang transform
Noninvasive cuffless blood pressure estimation using pulse transit time and Hilbert-Huang transform
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DOI：
10.1016/j.compeleceng.2012.09.005
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发表时间：
2013-01-01
影响因子：
4.3
通讯作者：
Ko, Seokbum
中科院分区：
文献类型：
--
作者：
Choi, Younhee;Zhang, Qiao;Ko, Seokbum
人们普遍认为，从心电图（ECG）的R波峰值到光电体积描记图（PPG）的特征点的脉搏传导时间（PTT）与动脉僵硬度有关，可用于估计血压。希尔伯特黄变换 (HHT) 是一种很有前景的信号处理技术，可用于分析本质上非线性和非平稳的 ECG 和 PPG 数据。本文阐述了血压与PTT之间的关系，并讨论了校准和重新校准的问题。此外，采用多重创新的递归最小二乘算法来更新模型的未知参数向量，改善结果。基于MIMIC数据库的连续数据对我们的算法进行了测试，并计算了准确性以验证所提出的方法。 (C) 2012 Elsevier Ltd. 保留所有权利。
It is widely accepted that pulse transit time (PTT), from the R wave peak of electrocardiogram (ECG) to a characteristic point of photoplethysmogram (PPG), is related to arterial stiffness, and can be used to estimate blood pressure. A promising signal processing technology, Hilbert Huang transform (HHT), is introduced to analyze both ECG and PPG data, which are inherently nonlinear and non-stationary. The relationship between blood pressure and PTT is illustrated, and the problems of calibration and re-calibration are also discussed in this paper. Moreover, multi-innovation recursive least square algorithm is employed to update the unknown parameter vector for the model and improve the results. Our algorithm is tested based on the continuous data from MIMIC database, and the accuracy is calculated to validate the proposed method. (C) 2012 Elsevier Ltd. All rights reserved.