ANNを用いた透析シャント音による狭窄診断支援システムの要素研究  [in Japanese] Elemental Study on Auscultaiting Diagnosis Support System of Hemodialysis Shunt Stenosis by ANN  [in Japanese]

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Author(s)

Abstract

It is desired to detect stenosis at an early stage to use hemodailysis shunt for longer time. Stethoscope auscultation of vascular murmurs is useful noninvasive diagnostic approach, but an experienced expert operator is necessary. Some experts often say that the high-pitch murmurs exist if the shunt becomes stenosed, and some studies report that there are some features detected at high frequency by time-frequency analysis. However, some of the murmurs are difficult to detect, and the final judgment is difficult. This study proposes a new diagnosis support system to screen stenosis by using vascular murmurs. The system is performed using artificial neural networks (ANN) with the analyzed frequency data by maximum entropy method (MEM). The author recorded vascular murmurs both before percutaneous transluminal angioplasty (PTA) and after. Examining the MEM spectral characteristics of the high-pitch stenosis murmurs, three features could be classified, which covered 85 percent of stenosis vascular murmurs. The features were learnt by the ANN, and judged. As a result, a percentage of judging the classified stenosis murmurs was 100%, and that of normal was 86%.

Journal

  • IEEJ Transactions on Electronics, Information and Systems

    IEEJ Transactions on Electronics, Information and Systems 130(3), 401-406, 2010-03-01

    The Institute of Electrical Engineers of Japan

References:  16

Cited by:  4

Codes

  • NII Article ID (NAID)
    10026228213
  • NII NACSIS-CAT ID (NCID)
    AN10065950
  • Text Lang
    JPN
  • Article Type
    Journal Article
  • ISSN
    03854221
  • NDL Article ID
    10600370
  • NDL Source Classification
    ZN31(科学技術--電気工学・電気機械工業)
  • NDL Call No.
    Z16-795
  • Data Source
    CJP  CJPref  NDL  J-STAGE 
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