Title :
Residual Stenosis Estimation of Arteriovenous Grafts Using a Dual-Channel Phonoangiography With Fractional-Order Features
Author :
Yi-Chun Du ; Wei-Ling Chen ; Chia-Hung Lin ; Chung-Dann Kan ; Ming-Jui Wu
Author_Institution :
Dept. of Electr. Eng., Southern Taiwan Univ. of Sci. & Technol., Tainan, Taiwan
Abstract :
The residual stenosis estimation of an arteriovenous shunt is a valuable for evaluating outcomes of percutaneous transluminal angioplasty (PTA) treatment and surgical revision. This paper proposes a dual-channel phonoangiography (PCG) with fractional-order features to estimate the residual of stenosis estimation of arteriovenous shunt. The auscultation technique provides a noninvasive tool to monitor the degrees of arteriovenous grafts (AVGs). Then, support methods, such as the Burg autoregressive (AR) method and self-synchronization error formulation (SSEF), are used to extract fractional-order features between the loop site (L-site) and venous anastomosis site (V-site). Using 2-D patterns (nonlinear mapping), a generalized regression neural network (GRNN) is designed as a nonlinear estimate model to indicate the outcome of surgical revision or AVG stenosis upon routine monthly examinations. For 42 long-term follow-up patients, the results of examination show the proposed GRNN-based screening model efficiently estimates residual stenosis.
Keywords :
bioacoustics; biomedical ultrasonics; blood vessels; feature extraction; neural nets; patient treatment; regression analysis; 2D patterns; AVG stenosis; Burg autoregressive method; PTA treatment; arteriovenous grafts; arteriovenous shunt; auscultation technique; dual-channel phonoangiography; fractional-order feature extraction; generalized regression neural network; loop site; nonlinear estimate model; nonlinear mapping; percutaneous transluminal angioplasty; residual stenosis estimation; self-synchronization error formulation; surgical revision; venous anastomosis site; Cities and towns; Estimation; Indexes; Informatics; Monitoring; Stethoscope; Surgery; Arteriovenous graft (AVG); fractional-order feature; generalized regression neural network (GRNN); phonoangiography (PCG);
Journal_Title :
Biomedical and Health Informatics, IEEE Journal of
DOI :
10.1109/JBHI.2014.2328346