Department of Electronics Engineering, Kookmin University, Seoul 02707, Korea.
Sensors (Basel). 2022 Feb 4;22(3):1175. doi: 10.3390/s22031175.
Blood pressure measurements are one of the most routinely performed medical tests globally. Blood pressure is an important metric since it provides information that can be used to diagnose several vascular diseases. Conventional blood pressure measurement systems use cuff-based devices to measure the blood pressure, which may be uncomfortable and sometimes burdensome to the subjects. Therefore, in this study, we propose a cuffless blood pressure estimation model based on Monte Carlo simulation (MCS). We propose a heterogeneous finger model for the MCS at wavelengths of 905 nm and 940 nm. After recording the photon intensities from the MCS over a certain range of blood pressure values, the actual photoplethysmography (PPG) signals were used to estimate blood pressure. We used both publicly available and self-made datasets to evaluate the performance of the proposed model. In case of the publicly available dataset for transmission-type MCS, the mean absolute errors are 3.32 ± 6.03 mmHg for systolic blood pressure (SBP), 2.02 ± 2.64 mmHg for diastolic blood pressure (DBP), and 1.76 ± 2.8 mmHg for mean arterial pressure (MAP). The self-made dataset is used for both transmission- and reflection-type MCSs; its mean absolute errors are 2.54 ± 4.24 mmHg for SBP, 1.49 ± 2.82 mmHg for DBP, and 1.51 ± 2.41 mmHg for MAP in the transmission-type case as well as 3.35 ± 5.06 mmHg for SBP, 2.07 ± 2.83 mmHg for DBP, and 2.12 ± 2.83 mmHg for MAP in the reflection-type case. The estimated results of the SBP and DBP satisfy the requirements of the Association for the Advancement of Medical Instrumentation (AAMI) standards and are within Grade A according to the British Hypertension Society (BHS) standards. These results show that the proposed model is efficient for estimating blood pressures using fingertip PPG signals.
血压测量是全球最常见的医学检测之一。血压是一个重要的指标，因为它提供的信息可用于诊断多种血管疾病。传统的血压测量系统使用基于袖带的设备来测量血压，这可能会让受测者感到不适，有时甚至带来负担。因此，在这项研究中，我们提出了一种基于蒙特卡罗模拟（MCS）的无袖带血压估计模型。我们提出了一种在 905nm 和 940nm 波长下用于 MCS 的异质手指模型。在记录了一定范围内血压值的 MCS 光子强度后，使用实际的光体积描记图（PPG）信号来估计血压。我们使用了公开可用数据集和自制数据集来评估所提出模型的性能。对于公开的传输式 MCS 数据集，收缩压（SBP）的平均绝对误差为 3.32±6.03mmHg，舒张压（DBP）为 2.02±2.64mmHg，平均动脉压（MAP）为 1.76±2.8mmHg。自制数据集用于传输式和反射式 MCS；对于传输式，SBP 的平均绝对误差为 2.54±4.24mmHg，DBP 为 1.49±2.82mmHg，MAP 为 1.51±2.41mmHg；对于反射式，SBP 的平均绝对误差为 3.35±5.06mmHg，DBP 为 2.07±2.83mmHg，MAP 为 2.12±2.83mmHg。SBP 和 DBP 的估计结果符合医疗器械促进协会（AAMI）标准的要求，根据英国高血压学会（BHS）标准，属于 A 级。这些结果表明，所提出的模型使用指尖 PPG 信号来估计血压是有效的。
