Research on the Method of Blood Pressure Monitoring Based on Multiple Parameters of Pulse Wave_Journal of Biomedical Engineering

Authors：

MIAOChangyun ¹ , MUDianwei ¹ ,  ZHANGCheng ¹ , MIAOChunjiao ² , LIHongqiang ¹

1. School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, China;
2. School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044, China;

Corresponding author：

ZHANGCheng, Email: zhangchengly730@aliyun.com

Keywords：

blood pressure measure; multiple characteristic parameters of pulse wave; phonocardiography; calculation model of human blood pressure; wearable device

DOI：

10.7507/1001-5515.20150197

Video：

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Abstract Full text Figures/Tables Video References Cited by

In order to improve the accuracy of blood pressure measurement in wearable devices, this paper presents a method for detecting blood pressure based on multiple parameters of pulse wave. Based on regression analysis between blood pressure and the characteristic parameters of pulse wave, such as the pulse wave transit time (PWTT), cardiac output, coefficient of pulse wave, the average slope of the ascending branch, heart rate, etc. we established a model to calculate blood pressure. For overcoming the application deficiencies caused by measuring ECG in wearable device, such as replacing electrodes and ECG lead sets which are not convenient, we calculated the PWTT with heart sound as reference (PWTT_PCG). We experimentally verified the detection of blood pressure based on PWTT_PCG and based on multiple parameters of pulse wave. The experiment results showed that it was feasible to calculate the PWTT from PWTT_PCG. The mean measurement error of the systolic and diastolic blood pressure calculated by the model based on multiple parameters of pulse wave is 1.62 mm Hg and 1.12 mm Hg, increased by 57% and 53% compared to those of the model based on simple parameter. This method has more measurement accuracy.

Citation： MIAOChangyun, MUDianwei, ZHANGCheng, MIAOChunjiao, LIHongqiang. Research on the Method of Blood Pressure Monitoring Based on Multiple Parameters of Pulse Wave. Journal of Biomedical Engineering, 2015, 32(5): 1113-1117. doi: 10.7507/1001-5515.20150197 Copy

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9.	HENNIG A, PATZAK A. Continuous blood pressure measurement using pulse transit time[J]. Somnologie-Schlafforschung und Schlafmedizin, 2013, 17(2):104-110.
10.	郭兴明,丁晓蓉,钟丽莎,等.小波包与混沌集成的心音特征提取及分类识别[J].仪器仪表学报,2012,33(9):1938-1944.
11.	O'ROURKE M F. Time domain analysis of the arterial pulse in clinical medicine[J]. Medical & Biological Engineering & Computing, 2009, 47(2):119-129.
12.	KIM J S, CHEE Y J, PARK J W, et al. A new approach for non-intrusive monitoring of blood pressure on a toilet seat[J]. Physiological Measurement, 2006, 27(2):203-211.
13.	汤池,杨国胜,王跃民,等.利用逐步回归法分析家兔血压和脉搏波特征参数的相关性[J].第四军医大学学报,2005,26(6):568-570.
14.	刘宝华,朱红莲,任晓华.小波用于脉搏波速度测量及去噪[J].生物医学工程学杂志,2011,28(1):54-57.
15.	FIALA J, BINGGER P, RUH D, et al. An implantable optical blood pressure sensor based on pulse transit time[J]. Biomedical Microdevices, 2013, 15(1):73-81.
16.	PAYNE R A, SYMEONIDES C N, WEBB D J, et al. Pulse transit time measured from the ECG:an unreliable marker of beat-to-beat blood pressure[J]. Journal of Applied Physiology, 2006, 100(1):136-141.
17.	焦学军,房兴业.利用脉搏波特征参数连续测量血压的方法研究[J].生物医学工程学杂志,2002,19(2):217-220.

1. PANTELOPOULOS A, BOURBAKIS N G. A survey on wearable sensor based systems for health monitoring and prognosis[J]. IEEE Transactions on Systems Man and Cybernetics Part C Applications and Reviews, 2010, 40(1):1-12.
2. 张大伟,陈佳品,冯洁,等.面向准危重病人的区域化无线监护系统研制[J].仪器仪表学报,2014,35(1):74-81.
3. ANLIKER U, WARD J A, LUKOWICZ P, et al. AMON:a wearable multiparameter medical monitoring and alert system[J]. Information Technology in Biomedicine, IEEE Transactions on, 2004, 8(4):415-427.
4. WILHELM F H, PFALTZ M C, GROSSMAN P. Continuous electronic data capture of physiology, behavior and experience in real life:toward ecological momentary assessment of emotion[J]. Interacting Comput, 2006, 18(3):171-178.
5. SHI Y, ZHAO Z, FANG Z, et al. A full parameter body sensor network system and its environmental tests[C]//Proceedings of 2012 International Conference on Measurement, Information and Control. Harbin, China:2012, 1:30-33.
6. GU W B, POON C C Y, SY M Y, et al. A h-shirt based body sensor network for cuffless calibration and estimation of arterial blood pressure[C]//2009 Sixth International Workshop on Wearable & Implantable Body Sensor Networks Conference (BSN 2009). Berkeley, CA:2009:151-155.
7. NEMATI E, DEEN M J, MONDAL T. A wireless wearable ECG sensor for long term applications[J]. Communications Magazine, IEEE, 2012, 50(1):36-43.
8. 张政波,王步青,王卫东,等.心肺交互作用综合测试系统[J].生物医学工程学杂志,2013,30(2):395-402.
9. HENNIG A, PATZAK A. Continuous blood pressure measurement using pulse transit time[J]. Somnologie-Schlafforschung und Schlafmedizin, 2013, 17(2):104-110.
10. 郭兴明,丁晓蓉,钟丽莎,等.小波包与混沌集成的心音特征提取及分类识别[J].仪器仪表学报,2012,33(9):1938-1944.
11. O'ROURKE M F. Time domain analysis of the arterial pulse in clinical medicine[J]. Medical & Biological Engineering & Computing, 2009, 47(2):119-129.
12. KIM J S, CHEE Y J, PARK J W, et al. A new approach for non-intrusive monitoring of blood pressure on a toilet seat[J]. Physiological Measurement, 2006, 27(2):203-211.
13. 汤池,杨国胜,王跃民,等.利用逐步回归法分析家兔血压和脉搏波特征参数的相关性[J].第四军医大学学报,2005,26(6):568-570.
14. 刘宝华,朱红莲,任晓华.小波用于脉搏波速度测量及去噪[J].生物医学工程学杂志,2011,28(1):54-57.
15. FIALA J, BINGGER P, RUH D, et al. An implantable optical blood pressure sensor based on pulse transit time[J]. Biomedical Microdevices, 2013, 15(1):73-81.
16. PAYNE R A, SYMEONIDES C N, WEBB D J, et al. Pulse transit time measured from the ECG:an unreliable marker of beat-to-beat blood pressure[J]. Journal of Applied Physiology, 2006, 100(1):136-141.
17. 焦学军,房兴业.利用脉搏波特征参数连续测量血压的方法研究[J].生物医学工程学杂志,2002,19(2):217-220.

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