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Cuff-less continuous measurement of blood pressure using wrist and fingertip photo-plethysmograms: Evaluation and feature analysis

机译:使用腕部和指尖光体积描记图无袖带式连续测量血压:评估和特征分析

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Continuous monitoring of blood pressure improves prevention and control of cardiovascular diseases. Currently, cuff-based oscillometric sphygmomanometers are commonly used to monitor the systolic and diastolic blood pressure. However, this technique is discontinuous in nature and inconvenient for repeated measurements. Here we have proposed indirect measurement of blood pressure from photo-plethysmograms (PPG) simultaneously recorded from wrist and fingertip. The signals were recorded from 111 participants and different morphological features were obtained from PPG and its second derivative, acceleration plethysmograms (APG). Moreover, different measures of pulse transit time (PTT) and pulse wave velocity (PWV) were obtained from the recorded PPGs. Multi-layer Neural Networks were used to estimate the non-linear relationship between these features and systolic and diastolic blood pressures (SBP and DBP). Mean absolute errors of 6.77 and 4.82 mmHg were achieved in comparison with measurements from a validated commercial oscillometric sphygmomanometer. Feature analysis provided insight about the importance of features for estimating BP, and demonstrated that these features are not the same for SBP and DBP. Using the highest-ranked 15 and 13 features obtained from moving-backward algorithm the mean absolute errors were reduced to 5.31 and 4.62 mmHg for SBP and DBP. However, the optimum optimal feature sets provided by a genetic algorithm for estimating SBP/DBP led to the lowest mean absolute errors of 4.94/4.03. These results compared to previous studies and the available standards suggest that the method is a promising substitute for oscillometric sphygmomanometers which can be used conveniently for continuous monitoring of blood pressure. (C) 2018 Elsevier Ltd. All rights reserved.
机译:持续监测血压可以改善心血管疾病的预防和控制。当前,基于袖带的脉搏血压计通常用于监测收缩压和舒张压。然而,该技术本质上是不连续的,并且不便于重复测量。在这里,我们提出了通过同时从手腕和指尖记录的光电容积描记图(PPG)间接测量血压的方法。记录了来自111位参与者的信号,并从PPG及其二阶导数,加速体积描记图(APG)获得了不同的形态特征。此外,从记录的PPG中获得了不同的脉冲传播时间(PTT)和脉搏波速度(PWV)度量。多层神经网络用于估计这些特征与收缩压和舒张压(SBP和DBP)之间的非线性关系。与经过验证的商用示波血压计的测量值相比,平均绝对误差为6.77和4.82 mmHg。特征分析提供了有关特征对于估计BP重要性的见解,并证明了这些特征对于SBP和DBP是不同的。使用从向后移动算法获得的最高排名的15和13个特征,SBP和DBP的平均绝对误差降低到5.31和4.62 mmHg。但是,遗传算法提供的用于估计SBP / DBP的最佳最佳特征集导致最低的平均绝对误差为4.94 / 4.03。与以前的研究和现有标准相比,这些结果表明该方法是示波法血压计的有希望的替代品,该示波血压计可方便地用于连续监测血压。 (C)2018 Elsevier Ltd.保留所有权利。

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