Estimating Physical Characteristics with Body-worn Accelerometers Based on Activity Similarities

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This paper describes our experimental investigation of the end user physical characteristics (e.g., gender, height, weight, dominant hand, and skill at sport) that can be successfully estimated solely from sensor data obtained during daily activities (e.g., walking and dish washing) from body-worn accelerometers. For this purpose we use the huge quantities of data that we have collected, which include 14,880 labeled activities obtained from 61 subjects. Our proposed method tries to estimate various kinds of characteristics based on our simple idea ‘When the activity sensor data of two users are similar, the physical characteristics of the two users may also be similar.’ We consider that estimating the end user's physical characteristics will enable us to realize new kinds of applications that automatically recommend information/services to an end user according to her estimated physical characteristics such as gender and weight. \n------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.24(2016) No.2 (online)------------------------------

This paper describes our experimental investigation of the end user physical characteristics (e.g., gender, height, weight, dominant hand, and skill at sport) that can be successfully estimated solely from sensor data obtained during daily activities (e.g., walking and dish washing) from body-worn accelerometers. For this purpose we use the huge quantities of data that we have collected, which include 14,880 labeled activities obtained from 61 subjects. Our proposed method tries to estimate various kinds of characteristics based on our simple idea ‘When the activity sensor data of two users are similar, the physical characteristics of the two users may also be similar.’ We consider that estimating the end user's physical characteristics will enable us to realize new kinds of applications that automatically recommend information/services to an end user according to her estimated physical characteristics such as gender and weight. \n------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.24(2016) No.2 (online)------------------------------

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詳細情報 詳細情報について

  • CRID
    1050282812883738112
  • NII論文ID
    170000130872
  • NII書誌ID
    AN00116647
  • ISSN
    18827764
  • Web Site
    http://id.nii.ac.jp/1001/00148170/
  • 本文言語コード
    en
  • 資料種別
    journal article
  • データソース種別
    • IRDB
    • CiNii Articles

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