Noninvasive Continuous Blood Pressure Measurement Method Based on EEMD and ANN
-
摘要: 血压是衡量人体心血管系统功能的一个重要指标。该文针对电子血压计不能实现血压的无创连续测量等问题，提出一种基于EEMD和ANN算法的无创血压测量方法。实验分析了MIMIC数据库中的19 500个脉搏波信号，通过EEMD对脉搏波进行分解，提取第4层分解信号的10个特征参数作为ANN的输入，脉搏波对应的血压作为ANN的输出进行血压模型的训练，并对模型进行误差分析。实验结果表明，模型的测试误差达到美国医疗器械促进协会（AAMI）制定的标准，通过该方法可实现血压的无创连续测量。Abstract: Blood pressure is an important index to measure the function of human cardiovascular system. In order to solve the problem of non-invasive continuous measurement of blood pressure in electronic sphygmomanometer, a noninvasive blood pressure measurement method based on EEMD (ensemble empirical mode decomposition) and ANN (artificial neural networks) were proposed. In the experiment, a total of 19 500 pulse wave signals from THE MIMIC DATABASE were analyzed and subsequently the pulse wave was decomposed by EEMD. Furthermore, 10 characteristic parameters of the 4th layer decomposition signal were extracted as the input of ANN. The blood pressure corresponding to the pulse wave was taken as the output of ANN to train the BP (blood pressure) model. The error analysis of the model was carried out. The results indicated that the error of the model meets the standards of the American Association for the advancement of medical instrumentation (AAMI). Therefore, this method can be employed in noninvasive continuous measurement of blood pressure.
-
-
[1] 段于千, 胡平平. 无创血压测量示波法分析与研究[J]. 微计算机信息, 2011, 27(1):102-103. [2] Xu L, Gao K. Continuous cuffless arterial blood pressure measurement based on PPG quality assessment[J]. Int J Comput Biol Drug Design, 2015, 8(2):150-158.
[3] 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. [4] Lin H D, Lee Y S, Chuang B N. Using dual-antenna nanosecond pulse near-feld sensing technology for non-contact and continuous blood pressure measurement[C]//2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2012:219-222.
[5] 邹滋润, 陈真诚, 朱健铭. 基于光电容积脉搏波的呼吸波提[J]. 中国生物医学工程学报, 2013, 32(4):508-512. [6] 张天淼, 朱兰. 光体积描记术原理及应用[J]. 中国医疗器械杂志, 2016, 40(3):186-190. [7] 王步青, 柴晓珂, 张政波, 等. 心电图和光电容积脉搏波计算心率变异性的比较研究[J]. 中国医疗器械杂志, 2015, 39(4):249-252. [8] Yoon Y Z, Yoon G W. Nonconstrained blood pressure measurement by photoplethysmography[J]. J Opt Soc of Korea, 2006, 10(2):91-95.
[9] Fortino G, Giampa V. PPG-based methods for non invasive and continuous blood pressure measurement:an overview and development issues in body sensor networks[C]//Medical Measurements and Applications Proceedings (MeMeA), 2010 IEEE International Workshop on. IEEE, 2010:10-13.
[10] 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. [11] 罗志昌, 张松, 杨益民. 脉搏波的工程分析与临床应用[M]. 北京:科学出版社, 2006. [12] 陈仁祥, 汤宝平, 马婧华. 基于EEMD的振动信号自适应降噪方法[J]. 振动与冲击, 2012, 31(15):82-86. [13] 张碧薇. 基于EEMD与平稳小波变换的脉搏波形特征分析研究[D]. 北京:北京工业大学, 2013. [14] 季忠, 刘旭. 基于波形特征和小波的脉搏波特征点识别研究[J]. 仪器仪表学报, 2016, 37(2):379-386. [15] 徐可欣, 王继寸, 余辉, 等. 脉搏波时域特征与血压相关性的研究[J]. 中国医疗设备, 2009(8):42-45. [16] 周品. MATLAB神经网络设计与应用[M]. 北京:清华大学出版社, 2013. [17] 王丽萍. 基于BP神经网络工具箱实现函数逼近[J]. 湖南农机(学术版), 2011(5):29-31. [18] Madhav K V, Ram M R, Krishna E H, et al. Robust extraction of respiratory activity from ppg signals using modifed mspca[J]. IEEE Trans Instrument Measur, 2013, 62(5):1094-1106.
[19] Sayadi O, Shamsollahi M B. Utility of a nonlinear joint dynamical framework to model a pair of coupled cardiovascular signals[J]. IEEE J Biomed Health Inform, 2013, 17(4):881-890.
[20] Li P, Liu M, Zhang X, et al. Novel wavelet neural network algorithm for continuous and noninvasive dynamic estimation of blood pressure from photoplethysmography[J]. Sci Chin Inform Sci, 2016:59(4):1-10.
[21] Heusdens J F, Lof S, Pennekamp C W A, et al. Validation of non-invasive arterial pressure monitoring during carotid endarterectomy[J]. Brit J Anaesthesia, 2016, 117(3):316-323.
[22] Kurylyak Y, Lamonaca F, Grimaldi D. A neural networkbased method for continuous blood pressure estimation from a PPG signal[C]//2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). IEEE, 2013:280-283.
计量
- 文章访问数: 13
- HTML全文浏览量: 0
- PDF下载量: 3
下载:
