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Proceedings Paper

Elapsed time analysis of vascular stenosis by shunt sound using dynamic time warping and self-organizing map
Author(s): Yusaku Ando; Osamu Sakata; Yutaka Suzuki
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Paper Abstract

At the end of 2014, the number of Japanese dialysis patients was approximately 320,000, which is increasing every year. Chronic renal failure patients require hemodialysis because the workings of the kidney can't fall and take any more out a toxin in extracorporeal. During hemodialysis, vascular access is needed to secure enough blood. However, vascular access encounters the problem of hemadostenosis. Early detection of stenosis may facilitate long-term use of hemodialysis shunts. The stethoscope auscultation of vascular murmurs can be useful in the assessment of access patency; however, the sensitivity of this diagnostic approach is skill dependent. This study proposes a diagnosis system for assessing the progress of hemodialysis shunt stenosis to detect stenosis at its early stage by using vascular murmurs. The system is based on dynamic time warping (DTW), a self-organizing map (SOM), and a short-time maximum entropy method (STMEM) for data analysis. The SOM based on the spectrum of the blood flow sound obtained by STMEM qualitatively judges whether the blood vessel access of the dialysis patient is normal or abnormal. Moreover, by calculating the dissimilarity of spectrum using DTW, the narrowing of the blood vessel due to the time course of the dialysis patient is analyzed quantitatively. As a result, the degree of change in stenosis due to time course of dialysis patients could be confirmed from the qualitative aspect and the quantitative aspect. At the same time, it turned out that the blood vessel was stenotic even in a serious patient even immediately after surgery.

Paper Details

Date Published: 17 April 2019
PDF: 5 pages
Proc. SPIE 11071, Tenth International Conference on Signal Processing Systems, 1107103 (17 April 2019); doi: 10.1117/12.2516533
Show Author Affiliations
Yusaku Ando, Tokyo Univ. of Science (Japan)
Osamu Sakata, Tokyo Univ. of Science (Japan)
Yutaka Suzuki, Univ. of Yamanashi (Japan)


Published in SPIE Proceedings Vol. 11071:
Tenth International Conference on Signal Processing Systems
Kezhi Mao; Xudong Jiang, Editor(s)

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