A Method for Extracting Common Physical Activity Locations among Older People from GPS and Accelerometer Data

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  • Fukuoka Yutaka
    Department Electric and Electronic Engineering, Kogakuin University Department of Preventive Medicine and Public Health, Tokyo Medical University
  • Nishizawa Hayato
    Department Electric and Electronic Engineering, Kogakuin University
  • Tatsuya Nishizawa Eric
    Department Electric and Electronic Engineering, Kogakuin University
  • Amagasa Shiho
    Department of Preventive Medicine and Public Health, Tokyo Medical University Graduate School Public Health, Teikyo University
  • Murayama Hiroshi
    Tokyo Metropolitan Institute for Geriatrics and Gerontology
  • Fujiwara Takeo
    Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University
  • Inoue Shigeru
    Department of Preventive Medicine and Public Health, Tokyo Medical University
  • Shobugawa Yugo
    Graduate School of Medical and Dental Sciences, Niigata University

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Other Title
  • GPSおよび加速度データからの高齢者に共通の身体活動場所の抽出法
  • GPS オヨビ カソクド データ カラ ノ コウレイシャ ニ キョウツウ ノ シンタイ カツドウ バショ ノ チュウシュツホウ

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<p>Spatial data from a portable GPS logger have the potential to allow objective monitoring of locations where physical activity is taking place in a community. However, few studies have identified common physical activity locations visited by many people. This study aimed to propose a method for extracting such locations using GPS and accelerometer data using the k means method. The validity of the proposed method was examined using simulation data and then the method was applied to actual data obtained in a previous study. The participants in the previous study were healthy older people who wore GPS loggers and accelerometers for seven consecutive days. The k means method with various k was applied to the combined data of GPS and accelerometer to extract physical activity locations common to some participants. Simulation results indicated that the proposed method was able to extract locations where many participants performed physical activity of 3.0 METs or more. The results using the actual data from 50 participants also showed the validity of the proposed method.</p>

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