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Estimation of Arterial Viscosity Based on an Oscillometric Method and Its Application in Evaluating the Vascular Endothelial Function.

Hiroshi TanakaAkihisa MitoHarutoyo HiranoZu SohRyuji NakamuraNoboru SaekiMasashi KawamotoYukihito HigashiMasao YoshizumiToshio Tsuji
Published in: Scientific reports (2019)
This paper proposes an algorithm for estimating the arterial viscosity using cuff pressures and pulse waves measured by an automatic oscillometric sphygmomanometer. A change in the arterial viscosity during the enclosed-zone flow-mediated dilation test is calculated as an index for evaluating the vascular endothelial function %η. In all, 43 individuals participated in this study. After the index %η was calculated, the accuracy of the index %η in distinguishing healthy subjects and subjects at a high risk of arteriosclerosis was tested via a receiving operating characteristic (ROC) analysis. The calculated %η for the healthy participants and those at a high risk of arteriosclerosis was 13.4 ± 55.1% and -32.7 ± 34.0% (mean ± S.D.), respectively. The area under the ROC curve was 0.77. Thus, it was concluded that the proposed method can be used to evaluate the vascular endothelial function.
Keyphrases
  • machine learning
  • deep learning
  • blood pressure
  • neural network