Guo Cheng-Yan, Chang Hao-Ching, Wang Kuan-Jen, Hsieh Tung-Li
Accurate Meditech Inc., New Taipei City 241406, Taiwan.
Department of Electronic Engineering, National Kaohsiung University of Science and Technology, No. 415, Jiangong Rd., Sanmin Dist., Kaohsiung City 807618, Taiwan.
Micromachines (Basel). 2022 Aug 16;13(8):1327. doi: 10.3390/mi13081327.
Blood pressure (BP) data can influence therapeutic decisions for some patients, while non-invasive devices that continuously monitor BP can provide patients with a more comprehensive BP assessment. Therefore, this study proposes a multi-sensor-based small cuffless BP monitoring device that integrates a piezoelectric sensor array and an optical sensor, which can monitor the patient's physiological signals from the radial artery.
Based on the Moens-Korteweg (MK) equation of the hemodynamic model, pulse wave velocity (PWV) can be correlated with arterial compliance and BP can be estimated. Therefore, the novel method proposed in this study involves using a piezoelectric sensor array to measure the PWV and an optical sensor to measure the photoplethysmography (PPG) intensity ratio (PIR) signal to estimate the participant's arterial parameters. The parameters measured by multiple sensors were combined to estimate BP based on the P-β model derived from the MK equation.
We recruited 20 participants for the BP monitoring experiment to compare the performance of the BP estimation method with the regression model and the P-β model method with arterial compliance. We then compared the estimated BP with a reference device for validation. The results are presented as the error mean ± standard deviation (SD). Based on the regression model method, systolic blood pressure (SBP) was 0.32 ± 5.94, diastolic blood pressure (DBP) was 2.17 ± 6.22, and mean arterial pressure (MAP) was 1.55 ± 5.83. The results of the P-β model method were as follows: SBP was 0.75 ± 3.9, DBP was 1.1 ± 3.12, and MAP was 0.49 ± 2.82.
According to the results of our proposed small cuffless BP monitoring device, both methods of estimating BP conform to ANSI/AAMI/ISO 81060-2:20181_5.2.4.1.2 criterion 1 and 2, and using arterial parameters to calibrate the MK equation model can improve BP estimate accuracy. In the future, our proposed device can provide patients with a convenient and comfortable BP monitoring solution. Since the device is small, it can be used in a public place without attracting other people's attention, thereby effectively improving the patient's right to privacy, and increasing their willingness to use it.
血压(BP)数据会影响部分患者的治疗决策,而持续监测血压的无创设备可为患者提供更全面的血压评估。因此,本研究提出一种基于多传感器的小型无袖带血压监测设备,该设备集成了压电传感器阵列和光学传感器,可从桡动脉监测患者的生理信号。
基于血液动力学模型的莫恩斯 - 科特韦格(MK)方程,脉搏波速度(PWV)可与动脉弹性相关联,进而可估算血压。因此,本研究提出的新方法包括使用压电传感器阵列测量PWV,以及使用光学传感器测量光电容积脉搏波描记法(PPG)强度比(PIR)信号,以估算参与者的动脉参数。将多个传感器测量的参数相结合,基于从MK方程推导的P-β模型估算血压。
我们招募了20名参与者进行血压监测实验,以比较血压估算方法与回归模型以及具有动脉弹性的P-β模型方法的性能。然后将估算的血压与参考设备进行比较以进行验证。结果以误差均值±标准差(SD)表示。基于回归模型方法,收缩压(SBP)为0.32±5.94,舒张压(DBP)为2.17±6.22,平均动脉压(MAP)为1.55±5.83。P-β模型方法的结果如下:SBP为0.75±3.9,DBP为1.1±3.12,MAP为0.49±2.82。
根据我们提出的小型无袖带血压监测设备的结果,两种血压估算方法均符合ANSI/AAMI/ISO 81060 - 2:20181_5.2.4.1.2标准1和标准2,并且使用动脉参数校准MK方程模型可提高血压估算准确性。未来,我们提出的设备可为患者提供便捷舒适的血压监测解决方案。由于该设备体积小,可在公共场所使用而不引起他人注意,从而有效提高患者的隐私权,并增加他们使用的意愿。