• DocumentCode
    130128
  • Title

    The feasibility for dicrotic augmentation index to replace tidal augmentation index

  • Author

    Yingfei Su ; Yahui Zhang ; Yueming Jin ; Yang Yao ; Ruifeng Zhang ; Yongsheng Jiang ; Lisheng Xu

  • Author_Institution
    Sino-Dutch Biomed. & Inf. Eng. Sch., Northeastern Univ., Shenyang, China
  • fYear
    2014
  • fDate
    28-30 July 2014
  • Firstpage
    943
  • Lastpage
    948
  • Abstract
    Aortic augmentation index (AI) has great significance in predicting cardiovascular diseases. To obtain AI the tidal wave crest will be need, which is difficult to identify sometimes. Fortunately, it is easier to obtain the dicrotic wave crest, which can derive a parameter called dicrotic augmentation index (DAI). In this paper the AIs and DAIs of the pulse waves acquired from 20 subjects including young healthy volunteers (n=20), were compared. The differential method combined with threshold was employed to extract the key feature points. Then the value of AI and DAI can be calculated. Their linearly dependent coefficient was estimated by using the weighted least square method, and the consistency check was performed by t-test and Bland-Altman algorithm. It is notable that the values of AI and DAI are in acceptable agreement (R=0.672), and the dependent equation is y=-0.0045+0.7528x (x and y represents AI and DAI, respectively). However, the agreement varied with the postures of volunteers. In the standing and sitting postures, the agreements were not as close as that corresponding to the posture of lying. The R corresponding to the standing and sitting postures is 0.48 and 0.50, respectively; while the R corresponding to the lying posture of the volunteer is 0.67, demonstrating a closer agreement.
  • Keywords
    blood vessels; cardiovascular system; diseases; feature extraction; least squares approximations; medical signal processing; Bland-Altman algorithm; DAI value; aortic augmentation index; cardiovascular diseases; consistency check; dicrotic augmentation index; dicrotic wave crest; differential method; feature point extraction; linearly dependent coefficient; lying posture; pulse waves; sitting postures; standing postures; t-test; tidal augmentation index; tidal wave crest; weighted least square method; Artificial intelligence; Correlation; Educational institutions; Equations; Indexes; Market research; Mathematical model; Augmentation Index; Bland-Altman algorithm; Dicrotic Augmentation Index; correlation analysis; weighted least square method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation (ICIA), 2014 IEEE International Conference on
  • Conference_Location
    Hailar
  • Type

    conf

  • DOI
    10.1109/ICInfA.2014.6932787
  • Filename
    6932787