计算机科学 ›› 2017, Vol. 44 ›› Issue (10): 51-54.doi: 10.11896/j.issn.1002-137X.2017.10.009

• 生物信息学 • 上一篇    下一篇

隐蔽脉搏波潮波定位研究

郑刚,范琳琳,孙莹,戴敏   

  1. 天津理工大学天津市智能计算及软件新技术重点实验室 天津300384;天津理工大学计算机科学与工程学院 天津300384,天津理工大学天津市智能计算及软件新技术重点实验室 天津300384;天津理工大学计算机科学与工程学院 天津300384,天津理工大学计算机科学与工程学院 天津300384;中国民航大学中国民航信息技术科研基地 天津300300,天津理工大学天津市智能计算及软件新技术重点实验室 天津300384;天津理工大学计算机科学与工程学院 天津300384
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受天津市自然科学基金(16JCYBJC15300,15JCYBJC15800),中国民航大学省部级科研机构开放基金(CAAC-ITRB-201603)资助

Study of Hidden Tidal Wave Orientaion in Pulse Wave

ZHENG Gang, FAN Lin-lin, SUN Ying and DAI Min   

  • Online:2018-12-01 Published:2018-12-01

摘要: 中心动脉压的临床医学意义虽大于传统肱动脉和桡动脉血压,但其推算方法一直以来受基于有创伤数据的通用转换函数(General Transform Function,GTF)的建立和桡动脉脉搏波中隐蔽潮波位置的确定的约束。提出利用公开的有创伤中心动脉数据(麻省理工学院医学院的MIMIC重症监护数据,MIT MIMIC),通过傅里叶变换获得GTF,根据中心动脉收缩压数值,结合小波变换,反推脉搏波的隐蔽型潮波位置。研究发现,桡动脉脉搏波经小波sym4和haar变换后,其各自第3阶差值波的最大值后的第6个过零点为隐蔽型潮波位置。实验结果表明,利用所提方法获得隐蔽型潮波位置的识别准确率达到91.11%。

关键词: 潮波,MIMIC,传递函数,中心动脉压,脉搏波

Abstract: Although the clinical significance of central arterial pressure is superior to traditional brachial artery and radial artery blood pressure,its estimation method is bound by the establishment of GTF (General Transform Function) and the tidal wave position determination of radial artery wave.In this paper,GTF was obtained by Fourier transform on published traumatic central arterial data (MIT MIMIC,MIMIC Database(minicdb)),and according to the central arterial systolic pressure value,combining with wavelet transform on radial artery wave,tidal wave position was calcula-ted.It is found that the sixth zero crossing of the radial wave pulse wave after the sym4 and haar transformations on the radial pulse wave is the concealed tidal wave position after the maximum value of the third order difference wave.The experimental results show that the accuracy of the concealed tidal wave position recognition is up to 91.11%.

Key words: Tidal wave,MIMIC,GTF,Central arterial pressure,Pulse wave

[1] CHENG F,TAO J.Clinical Meaning of Central Aortic Pressure and Correlated Indices[J].Adv Cardiovasc Dis,2009,0(6):922-926.(in Chinese) 程飞,陶军.中心动脉压及其相关指标的临床意义[J].心血管病学进展,2009,30(6):922-926.
[2] SHAN X,WU J,YANG X,et al.Study of central aortic pressure in hypertensive patients and characteristic of radial artery pressure waveform in Traditional Chinese Medicine[C]∥Proceeding of IEEE International Conference on Control & Automation.IEEE Press,2014:1125-1130.
[3] LIU B,FUSUI J,LIN Y.Correlation between central aorticpressure and brachial artery pressure[J].Chinese Journal of Cardiovascular Medicine,2010,5(4):277-28.
[4] ANTSIPEROV V,MANSUROV G,P OLUPANOV A,et al.Noninvasive arterial blood pressure monitoring:By active sensor based on the principle of pulse wave compensation[C]∥proceeding of International Conference on Bioinformatics and Systems Biology.2016:1-5.
[5] CARLSEN R K,PETERS C D,KHATIR D S,et al.Estimated aortic blood pressure based on radial artery tonometry underestimates directly measured aortic blood pressure in patients with advancing chronic kidney disease staging and increasing arterialstiffness[J].Kidney International,2016,90(4):869-877.
[6] SALVI P,GRILLO A,PARATI G.Noninvasive estimation of central blood pressure and analysis of pulse waves by applanation tonometry[J].Hypertension Research,2015,38(10):646-648.
[7] HU F S.Non-invasive evaluation methos of large artery function based on pulse wave velocity and central arterial pressure[D].Hefei:University of Science and Technology of China,2016.(in Chinese) 胡福松.基于脉搏波速度和中心动脉压的大动脉功能无创评估方法研究[D].合肥:中国科学技术大学,2016.
[8] SUN W,TANG N,JIANG G P.Study of Characteristic PointIdentification and Preprocessing Method for Pulse Wave Signals[J].Journal of Biomedical Engineering,2015,2(1):197-201.(in Chinese) 孙薇,唐宁,江贵平.脉搏波信号特征点识别与预处理方法研究[J].生物医学工程学杂志,2015,2(1):197-201.
[9] JI Z,LIU X.Study on feature points recognition of pulse wave based on waveform feature and wavelet[J].Chinese Journal of Scientific Instrument,2016,7(2):379-386.(in Chinese) 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.
[10] 郑君里.信号与系统[M].北京:高等教育出版社,2000:117-176.
[11] ZHENG G,HUANG Q,YAN G,et al.Pulse waveform key point recognition by wavelet transform for central aortic blood pressure estimation[J].Journal of Information & ComputationalScience,2012,9(1):25-33.
[12] ZHAO Z,ZHENG G,PANG Y,et al.Study on Pulse Wave Signal Noise Reduction and Feature Point Identification[J].Journal of Convergence Information Technology,2013,8(9):953-960.
[13] ZHAO H,LI D Z,CHEN X C,et al.Sinus Bradycardia Detection Method Based on Photoplethysmography for Wearable Computing[J].Computer Science,2015,42(10):25-30.(in Chinese) 赵海,李大舟,陈星池,等.基于脉搏波的人体窦性心率过缓检测方法[J].计算机科学,2015,42(10):25-30.
[14] PELTOKANGAS M,VEHKAOJA A,VERHO J,et al.Age dependence of arterial pulse wave parameters extracted from dynamic blood pressure and blood volume pulse waves[J].IEEE Journal of Biomedical & Health Informatics,2015,1(1):142-149.
[15] KARAMANOGLU M,O’ROURKE M F,A VOLIO A P,et al.An analysis of the relationship between central aortic and peripheral upper limb pressure waves in man[J].European Heart Journal,1993,14(2):160-167.
[16] CHEB C H,NEVO E,FETICS B,et al.Estimation of Central Aortic Pressure Waveform by Mathematical Transformation of Radial Tonometry Pressure Validation of Generalized Transfer Function[J].Circulation,1997,95(7):1827-1836.
[17] GAO M,ROSE W C,FETICS B,et al.A Simple AdaptiveTransfer Function for Deriving the Central Blood Pressure Waveform from a Radial Blood Pressure Waveform[J].ScientificReports,2016,6:33230.
[18] HUOTARI M,MTT K,RNING J.Photoplethysmo-graphic measurements of arterial and aortic pulse waveform characteristics[J].Finnish Journal of Ehealth & Ewelfare,2015,7(2-3):83-87.
[19] WANG M Z,HE J X,ZHANG S T.The Choice of Best Multiwavelet Base in Image Compression[J].Computer Science,2002,9(s2):84-86.(in Chinese) 王梦哲,何甲兴,张淑婷.基于图像压缩的最佳多小波基选择[J].计算机科学,2002,29(s2):84-86.
[20] TANG X,SHU L,ZHENG W.Premature Best Signal Recognition Algorithm Based on Wavelet Transform and Rough Set[J].Computer Science,2015(b11):32-35.(in Chinese) 唐孝,舒兰,郑伟.基于小波变换和粗糙集的早搏信号识别算法[J].计算机科学,2015(b11):32-35.
[21] Kumar A,Singh M.Optimal Selection of Wavelet Function and Decomposition Level for Removal of ECG Signal Artifacts[J].Journal of Medical Imaging & Health Informatics,2015,5(1):138-146.
[22] ZHANG X,XU L,CHCNE K,et al.A New Method for Locating Feature Points in Pulse Wave Using Wavelet Transform[C]∥2009 WRI World Congress on Computer Science and Information Engineering.IEEE Press,2009:367-371.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!