Classification of Body Composition and Activity Patterns by Data Mining of Healthcare Data

DOI

Bibliographic Information

Other Title
  • ヘルスケアデータマイニングによる体組成と活動パターンの類型化

Abstract

Healthcare data is rapidly increasing as healthcare smart devices are developed. However, statistical analysis of healthcare big data is difficult due to heterogeneity in data quality and missing data. For such data, data mining methods such as clustering and dimension reduction may be useful as their preliminary analysis. In this paper, we show two illustrative applications; one is a principal component analysis of body composition data and the other is a latent topic analysis of hourly step-count dataset recorded by physical activity monitors. From those analyses, we proposed independent indices of body size and hidden obesity and extracted some diurnal patterns in ambulatory activities.

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Keywords

Details 詳細情報について

  • CRID
    1390282763106706688
  • NII Article ID
    130007631560
  • DOI
    10.11487/trafst.13.1_15
  • ISSN
    21896399
    18817610
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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