自己組織化マップと隠れマルコフモデルを用いた透析シャント音による血管狭窄診断支援装置

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2012/10/01

タイトル(英語): Auscultating Diagnosis for Hemodialysis Shunt Stenosis using a Self-Organizing Map and Hidden Markov Model

著者名: 脇　隼人（山梨大学大学院医学工学総合教育部），鈴木　裕（山梨大学総合分析実験センター），阪田　治（山梨大学大学院医学工学総合研究部），深澤　瑞也（山梨大学大学院医学工学総合研究部），加藤　初弘（山梨大学大学院医学工学総合研究部）

著者名(英語): Hayato Waki (University of Yamanashi), Yutaka Suzuki (University of Yamanashi), Osamu Sakata (University of Yamanashi), Mizuya Fukasawa (University of Yamanashi), Hatsuhiro Kato (University of Yamanashi)

キーワード: 透析シャント血流音，自己組織化マップ，メルケプストラム係数，隠れマルコフモデル　　vascular murmurs of hemodialysis shunt，self-organizing map，mel frequency cepstrum coefficient，hidden markov model

要約(英語): The number of dialysis patients is approximately 300,000 and is increasing every year in Japan. A renal failure patient requires a hemodialysis shunt for dialysis to be performed; however, the blood vessels around the hemodialysis shunt may become stenosed. The stethoscope auscultation of vascular murmurs has some use in the assessment of access patency; however, this diagnostic approach is skill dependent. Therefore, a diagnostic support system to detect stenosis is desirable. We developed an auscultating diagnosis support system for assessing hemodialysis shunt stenosis by using a self-organizing map (SOM) and short-time maximum entropy method. In this paper, for the purpose of improving the accuracy of stenosis detection, the Mel-frequency cepstrum coefficient (MFCC)-based hidden Markov model (HMM) was also used. As a result, a high correlation between an SOM system and HMM system was found. Therefore, the credibility of the each system was confirmed. Furthermore, the results indicated that the accuracy of stenosis detection could be improved by combining the SOM and HMM methods.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.132 No.10 （2012） 特集：医療関連電子技術のニュートピック

本誌掲載ページ: 1589-1594 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/132/10/132_1589/_article/-char/ja/