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Continuous Blood Pressure Monitoring using Wrist-worn Bio-impedance Sensors with Wet Electrodes

机译:使用带湿电极的腕戴式生物阻抗传感器进行连续血压监测

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Continuous blood pressure (BP) monitoring is essential for diagnosis and management of cardiovascular disorders. Currently, BP is measured using cuff-based methods, which are obtrusive and not suitable for continuous monitoring. Estimation of BP using pulse transit time (PTT) is a prominent method that eliminates the need for a cuff. In this paper, we present a new method to estimate BP based on PTT measurements from an array of 2×2 bio-impedance sensors placed on the wrist, which can be integrated into a small wearable device such as a smart watch for continuous BP monitoring. Diastolic and systolic BP were estimated using AdaBoost regression model based on PTT features extracted from the wrist bio-impedance signals. Data was collected from three participants using our custom bio-impedance sensors. Our method can estimate BP accurately with correlation coefficient, mean absolute error (MAE) and standard deviation (STD) of 0.92, 1.71 and 2.46 mmHg for the diastolic BP and 0.94, 2.57 and 4.35 mmHg for the systolic BP.
机译:连续血压(BP)监测对于诊断和管理心血管疾病至关重要。当前,使用基于袖带的方法来测量血压,这种方法具有干扰性,不适合连续监测。使用脉冲传输时间(PTT)估算BP是一种显着的方法,无需袖带。在本文中,我们提出了一种基于PTT测量的估算血压的新方法,该测量来自放置在手腕上的2×2个生物阻抗传感器阵列,可以将其集成到小型可穿戴设备中,例如用于连续BP监测的智能手表。基于从腕部生物阻抗信号中提取的PTT特征,使用AdaBoost回归模型估算舒张压和收缩压。使用我们的定制生物阻抗传感器从三名参与者中收集了数据。我们的方法可以以相关系数,平均绝对误差(MAE)和标准偏差(STD)分别评估舒张压的0.92、1.71和2.46 mmHg和收缩压的0.94、2.57和4.35 mmHg的BP进行准确估计。

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