Fuzzy Modeling of Acceleration Plethysmogram

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  • GONDA Eikou
    Department of Electrical and Computer Engineering, Yonago National College of Technology
  • MIYATA Hitoshi
    Department of Electrical and Computer Engineering, Yonago National College of Technology
  • MANIWA Yoshio
    Kurashiki Riverside Hospital
  • OHKITA Masaaki
    Department of Electrical and Electronic Engineering, Tottori University

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  • 加速度脈波のファジィモデリング
  • カソクド ミャクハ ノ ファジィ モデリング

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Abstract

The signals of acceleration plethysmogram is obtained as a fingertip content pulse wave detected by an optical sensor It is observed nonivasively and is used mainly for estimation of arteriosclerosis and blood vessel age. In the estimation and classification of acceleration plethysmogram, the traditional method has a problem that its method cannot classify the plethysmogram exactly because of imperfect sampling of its waveform. In this paper, the authors propose a method of applying fuzzy neural network to taking the precise waveform information in the classification of plethysmogram data. The authors add a technique of genetic algorithm to the optimization of fuzzy reasoning using the steepest descent method. In a technique using the genetic algorithm, the gene can select some kinds of MSFs. This method models acceleration plethysmogram and its chaos attractor In addition, the authors take the values of the waveform out of the modeling data as a vector, and classify the data of plethysmogram using self-organizing map. The advantages of this new method have been proved by comparing to the traditional method.

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