IEEE J Biomed Health Inform. 2018 Jul;22(4):1068-1074. doi: 10.1109/JBHI.2017.2714674. Epub 2017 Jun 12.
Using the massive MIMIC physiological database, we tried to validate pulse wave analysis (PWA) based on multiparameters model whether it can continuously estimate blood pressure (BP) values on single site of one hand. In addition, to consider the limitation of insufficient data acquirement for home user, we used pulse arrival time (PAT) driven BP information to determine the individual scale factors of the PWA-BP estimation model. Experimental results indicate that the accuracy of the average regression model has error standard deviations of mmHg (PAT), mmHg (PWA) for SBP and mmHg (PAT), mmHg (PWA) for DBP on 23 subjects over a 1 day period. We defined a local-model which is extracted regression model from sparsely selected small dataset, contrast to full dataset for 24h (average-model). The limit of BP estimation accuracy from the local-model of PWA is lower than that of PAT-BP average-model. Whereas the error of the BP estimation local-model was reduced using more data for scaling, it required more than four times the 1 min data extracted over the 12 h calibration period to predict BP for 1 day. This study shows that PWA has possibility to estimate BP value and PAT-driven BP information could be used to determine the individual scale factors of the PWA-BP estimation model for home users.
利用大规模 MIMIC 生理数据库,我们尝试验证基于多参数模型的脉搏波分析(PWA)是否可以在一只手上的单个部位连续估计血压(BP)值。此外,为考虑家用用户数据获取不足的限制,我们使用脉搏到达时间(PAT)驱动的 BP 信息来确定 PWA-BP 估计模型的个体比例因子。实验结果表明,在 23 名受试者的 1 天期间,平均回归模型的准确性具有标准偏差为 mmHg(PAT)、 mmHg(PWA)的 SBP 和标准偏差为 mmHg(PAT)、 mmHg(PWA)的 DBP。我们定义了一个局部模型,它是从稀疏选择的小数据集提取的回归模型,与 24 小时的全数据集(平均模型)相比。从 PWA 的局部模型进行 BP 估计的精度限制低于 PAT-BP 平均模型。然而,通过更多数据进行比例缩放可以降低 BP 估计局部模型的误差,但需要超过 12 小时校准期内提取的 1 分钟数据的四倍,才能预测 1 天的 BP。本研究表明,PWA 有可能估计 BP 值,并且 PAT 驱动的 BP 信息可用于确定家用用户的 PWA-BP 估计模型的个体比例因子。