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The Scientific World Journal
Volume 2014 (2014), Article ID 203148, 13 pages
Research Article

Multiple-Site Hemodynamic Analysis of Doppler Ultrasound with an Adaptive Color Relation Classifier for Arteriovenous Access Occlusion Evaluation

1Department of Biomedical Engineering, National Cheng Kung University, Tainan City 70101, Taiwan
2Department of Electrical Engineering, Southern Taiwan University of Science and Technology, Tainan City 71005, Taiwan
3Department of Internal Medicine, Kaohsiung Veterans General Hospital, Tainan Branch, Tainan City 71051, Taiwan
4Division of Infectious Diseases, Department of Medicine of Chi Mei Medical Center, Tainan City 71004, Taiwan
5Department of Electrical Engineering, Kao Yuan University, Kaohsiung City 82151, Taiwan

Received 28 February 2014; Accepted 24 March 2014; Published 30 April 2014

Academic Editors: H.-K. Lam, J. Li, and G. Ouyang

Copyright © 2014 Jian-Xing Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This study proposes multiple-site hemodynamic analysis of Doppler ultrasound with an adaptive color relation classifier for arteriovenous access occlusion evaluation in routine examinations. The hemodynamic analysis is used to express the properties of blood flow through a vital access or a tube, using dimensionless numbers. An acoustic measurement is carried out to detect the peak-systolic and peak-diastolic velocities of blood flow from the arterial anastomosis sites (A) to the venous anastomosis sites (V). The ratio of the supracritical Reynolds ( ) number and the resistive (Res) index quantitates the degrees of stenosis (DOS) at multiple measurement sites. Then, an adaptive color relation classifier is designed as a nonlinear estimate model to survey the occlusion level in monthly examinations. For 30 long-term follow-up patients, the experimental results show the proposed screening model efficiently evaluates access occlusion.