|
|
|
| Study on Multi-Mode Calculation Model in Non-Invasive Blood Pressure Measurement by Pulse Wave Velocity Method |
| Gu Yaxiong1* Yang Tao1 Bao Ke1 Zhong Xinxin2 |
1School of Mechatronic Engineering,Southwest Petroleum University, Chengdu 610500, China
2Operation Room,Chongqing Cancer Hospital,Chongqing 400030,China |
|
|
|
|
Abstract Aiming to solve the problem of modeling difficulties and low calculating accuracy in the process of blood pressure measurement by pulse wave velocity method, a new multi modulus model of blood pressure calculation was built up with combination of multiple modulus TPTT, ln(TPTT) and (1/TPTT)2. Firstly, the parameters for the model were determined based on experimental data drawn from measurement carried out to 99 random voluntary subjects while performance evaluation indexes of each model were calculated simultaneously. It was found that the fitting correlation coefficient of the modulus model, equal to 0.891, was larger than that of any other model with the least error variance of the modulus model, equal to 6.1, smaller than that of any other model, which showed that the multi modulus model possessed better fitting effect and lower calculation error compared with single modulus models. Then, another 36 subjects' SBP and DBP data were collected by using mercury blood meter and the self-designed multi modulus blood pressure system separately, and the relevant parameters between the two methods were calculated. For SBP, d<6 mmHg, Ed=0.55 mm Hg and δd=2.98 mmHg, while for DBP, d<6 mmHg, Ed=0.57 mmHg and δd=3.42 mmHg, which could meet the requirements included in AAMI SP10\|199. At last, the Bland-Altman difference method was applied to test the consistency of data between the two methods. A conclusion was drawn that 95% consistency limits of DBP and SBP were (-5.3, 6.4) and(7.2, -6.2) respectively, which satisfied the clinical demand and provided an evidence to the effectiveness of application of multi modulus model of blood pressure calculation in noninvasive blood pressure measurement. The research result proves that it is possible for multi modulus model of blood pressure calculation to be applied to noninvasive blood pressure measurement by pulse wave velocity method.
|
|
Received: 10 December 2015
|
|
|
|
|
|
[1] Chen Y, Wen C, Tao G, et al. Continuous and noninvasive measurement of systolic and diastolic blood pressure by one mathematical model with the same model parameters and two separate pulse wave velocities.[J]. Annals of Biomedical Engineering, 2012, 40(4):871-882.
[2] Zhang G, McCombie SA, Greenstein R, et al. Assessing the challenges of a pulse wave velocity based blood pressure measurement in surgical patients[C]//2014 36th Annual International Conference of the IEEE\|EMBS. Chicago: IEEE,2014: 574-577.
[3] 李顶立, 陈裕泉, 邢雷,等. 基于小波变换的无创血压检测方法研究[J]. 浙江大学学报:工学版, 2008, 42(9):1648-1652.
[4] 徐克, 周奇, 韦云隆. 无创血压测量[J]. 重庆工学院学报:自然科学版, 2008, 22(1):164-167.
[5] 徐久强, 蔺弘济, 李晗,等. 基于心电与脉搏波的血压检测算法的改进[J]. 东北大学学报:自然科学版, 2014, 35(1):33-37.
[6] Puke S, Suzuki T, Nakayama K, et al. Blood pressure estimation from pulse wave velocity measured on the chest[C]//2013 35th Annual International Conference of the IEEE\|EMBS. Osaka: IEEE, 2013: 6107-6110.
[7] 蒋巍巍, 季忠. 无创血压测量方法的研究进展[J]. 中华高血压杂志, 2015(7):685-689.
[8] Sola J, Proenca M, Ferrario D, et al. Noninvasive and non-occlusive blood pressure estimation via a chest sensor[J]. IEEE Transactions on Biomedical Engineering, 2013, 60(12): 3505-3513.
[9] 孟祥平. 利用脉搏波传播时间计算动脉血压的研究[J]. 中国生物医学工程学报, 2011,30(4):509-513.
[10] Payne RA, Symeonides CN, Webb DJ, 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.
[11] Mccombie DB, Shaltis PA, Reisner AT, et al. Adaptive hydrostatic blood pressure calibration: development of a wearable, autonomous pulse wave velocity blood pressure monitor.[J].2007, 53(4):370-373.
[12] 李顶立. 基于脉搏波的无创连续血压测量方法研究[D]. 杭州:浙江大学, 2008.
[13] 董骁, 宾光宇, 吴水才. 基于个性化脉搏波传导参数的连续血压测量方法研究[J]. 中国医疗设备, 2014,29(10):24-27.
[14] 朱雯, 阮晓声, 梁中庆,等. 脉动波在弹性管道中的传播速度与诸因素的关系[J]. 浙江大学学报:医学版, 1996,25(4):154-156.
[15] 白丽红, 王成, 文苗,等. 基于脉搏波传导时间的连续血压监测系统[J]. 生物医学工程研究, 2014,33(4):221-225.
[16] Chen MW, Kobayashi T, Ichikawa S, et al. Continuous estimation of systolic blood pressure using the pulse arrival time and intermittent calibration[J]. Medical and Biological Engineering and Computing, 2000, 38(5): 569-574.
[17] PoonCC Y, Zhang YT, Wong G, et al. The beat-to-beat relationship between pulse transit time and systolic blood pressure[C]//International Conference on Information Technology and Applications in Biomedicine. Oil: IEEE, 2008: 342-343.
[18] Kaniusas E, Pfützner H, Mehnen L, et al. Method for continuous nondisturbing monitoring of blood pressure by magnetoelastic skin curvature sensor and ECG[J]. Sensors Journal, 2006, 6(3): 819-828.
[19] Chen Y, Wen C, Tao G, et al. Continuous and noninvasive blood pressure measurement: a novel modeling methodology of the relationship between blood pressure and pulse wave velocity[J]. Annals of Biomedical Engineering, 2009, 37(11): 2222-2233.
[20] 倪平, 陈卉, 涂娇,等. 基于Bland-Altman法对定量资料的一致性评价及其SAS宏实现[J]. 中国临床药理学与治疗学, 2014, 19(8):898-903.
[21] Mukkamala R, Hahn JO, Inan OT, et al. Toward ubiquitous blood pressure monitoring via pulse transit time: theory and practice[J]. IEEE Transactions on Biomedical Engineering, 2015, 62(8): 1879-1901.
[22] Maguire M, Ward T, Markham C, et al. A comparative study in the use of brachial photoplethysmography and the QRS complex as timing references in determination of pulse transit time[C]//2001 23rd Annual International Conference of the IEEE\|EMBS.Istanbul: IEEE, 2001: 215-218.
[23] 刘有军, 乔爱科, 主海文,等. 颈动脉分支的血流动力学数值模拟[J]. 计算力学学报, 2004, 21(4):475-480.
[24] 李章俊, 王成, 朱浩,等. 基于光电容积脉搏波描记法的无创连续血压测量[J]. 中国生物医学工程学报, 2012, 31(4):607-614.
[25] 王晓东. 脉搏波的传播与反射及其在动脉硬化检测中的应用[D]. 济南:山东大学, 2007.
[26] 凌振宝, 张铭, 熊文激, 等. 基于脉搏波传导时间的无袖带血压测量仪设计[J]. 电子测量与仪器学报, 2013, 26(12): 1080-1085. |
|
|
|
