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Construction of the General Physical Condition Judgments System Using Acceleration Plethysmogram Analysis Results

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Neural Information Processing (ICONIP 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5864))

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Abstract

Among the popular lifestyle-related diseases are smoking, overweight and stress. A daily health check is important because there is no clear objective symptom for these diseases. We developed diagnostic software which shows the state of the blood vessels using a Basic SOM model, and compared 1map (Basic SOM) with Torus and a Spherical SOM (blossom).

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References

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Author information

Authors and Affiliations

  1. SOM Japan Inc.,  

    Heizo Tokutaka & Masaaki Ohkita

  2. Yonago National College of Technology,  

    Eikou Gonda

  3. Yabu City Minamidani Clinic,  

    Yoshio Maniwa

  4. Shikano-Onsen Hospital,  

    Masashi Yamamoto

  5. Tottori University, 4-637, Koyamacho-kita, Tottori, Japan

    Toshiyuki Kakihara, Masahumi Kurata, Kikuo Fujimura & Li Shigang

Authors
  1. Heizo Tokutaka
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  2. Eikou Gonda
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  3. Yoshio Maniwa
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  4. Masashi Yamamoto
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  5. Toshiyuki Kakihara
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  6. Masahumi Kurata
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  7. Kikuo Fujimura
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  8. Li Shigang
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  9. Masaaki Ohkita
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Editor information

Editors and Affiliations

  1. Department of Electronic Engineering, City University of Hong Kong, Hong Kong,  

    Chi Sing Leung

  2. School of Electrical Engineering and Computer Science, Kyungpook National University, 1370 Sankyuk-Dong, Puk-Gu, 702-701, Taegu, Korea

    Minho Lee

  3. School of Information Technology, King Mongkut’s University of Technology Thonburi, 126 Pracha-U-Thit Rd., Bangmod, Thungkru, 10140, Bangkok, Thailand

    Jonathan H. Chan

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© 2009 Springer-Verlag Berlin Heidelberg

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Tokutaka, H. et al. (2009). Construction of the General Physical Condition Judgments System Using Acceleration Plethysmogram Analysis Results. In: Leung, C.S., Lee, M., Chan, J.H. (eds) Neural Information Processing. ICONIP 2009. Lecture Notes in Computer Science, vol 5864. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10684-2_89

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  • DOI: https://doi.org/10.1007/978-3-642-10684-2_89

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10682-8

  • Online ISBN: 978-3-642-10684-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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