基于舒张期时间的个体化血压建模方法研究

发布时间：2018-10-18 19:19

【摘要】：本研究提出了一种基于脉搏波舒张期时间(diastolic time,DT)的无袖带式血压估计方法,能够有效提升可穿戴式设备的血压测量精度。该方案首先从脉搏波(photoplethysmography,PPG)中提取DT,再利用线性回归方法建立个体化血压估计模型。本研究对采集的30个样本的实验数据,进行血压建模并加以验证,实验结果显示收缩压的平均误差为1.859 mmHg,标准差为5.640 mmHg;舒张压的平均误差为1.049mmHg,标准差为6.107 mmHg,证明了该方案的可行性。通过将该方案的估计结果与基于脉搏波传导时间(pulse transit time,PTT)的血压模型的估算结果进行对比研究,结果表明交感神经活动较强时,基于DT的血压模型能够有效提升血压估计精度。
[Abstract]:In this study, a sleeveless band blood pressure estimation method based on pulse wave diastolic time (diastolic time,DT) is proposed, which can effectively improve the blood pressure measurement accuracy of wearable devices. Firstly, the DT, is extracted from the pulse wave (photoplethysmography,PPG) and then the individual blood pressure estimation model is established by linear regression method. In this study, blood pressure modeling and verification were carried out on the experimental data collected from 30 samples. The experimental results show that the mean error of systolic pressure is 1.859 mmHg, standard deviation is 5.640 mmHg; DBP average error is 1.049 mm Hg.The standard deviation is 6.107 mmHg, to prove the feasibility of this scheme. By comparing the estimated results of this scheme with those of the blood pressure model based on pulse wave conduction time (pulse transit time,PTT), the results show that the blood pressure model based on DT can effectively improve the accuracy of blood pressure estimation when sympathetic nerve activity is strong.
【作者单位】：中国科学院深圳先进技术研究院生物医学信息技术研究中心;华中科技大学光学与电子信息学院;
【基金】：国家自然科学基金资助项目(No.61502472)
【分类号】：R443.5

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