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Health Sensor Data Analysis for a Hospital and Developing Countries

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Smart Sensors and Systems

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Abstract

We present two types of sensor data analysis for medical and healthcare. One sensor dataset is collected in a hospital for medical purposes. We gathered accelerometer data and RFID data of real nursing in the hospital. We provide the real nursing dataset for mobile activity recognition which could be used for supervised machine learning, and also the big data combined with the patients’ medical records and sensors tried for 2 years. The other sensor dataset is collected in a developing country. We developed an eHealth system that comprises a set of sensor devices in an attache case. The first checkup was provided to 16,741 subjects. After 1 year, 2361 subjects participated in the second checkup, and the blood pressure of these subjects was significantly decreased (P < 0. 001). Based on these results we proposed a cost-effective method using a predictor, to ensure sustainability of the program in developing countries

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Authors and Affiliations

  1. Kyushu University Hospital, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 8128582, Japan

    Yasunobu Nohara & Naoki Nakashima

  2. Kyushu Institute of Technology, 1-1 Sensuicho, Tobata-ku, Kitakyushu, 8048550, Japan

    Sozo Inoue

Authors
  1. Yasunobu Nohara
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  2. Sozo Inoue
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  3. Naoki Nakashima
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Corresponding author

Correspondence to Yasunobu Nohara .

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Editors and Affiliations

  1. Center for Integrated Smart Sensors, Yuseong-gu, Daejeon, Korea (Republic of)

    Chong-Min Kyung

  2. System LSI Research Center, Kyushu University, Fukuoka, Japan

    Hiroto Yasuura

  3. Circuits and Systems Division, Tsinghua University, Beijing, China

    Yongpan Liu

  4. National Tsing Hua University , Hsichu, Taiwan

    Youn-Long Lin

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Nohara, Y., Inoue, S., Nakashima, N. (2017). Health Sensor Data Analysis for a Hospital and Developing Countries. In: Kyung, CM., Yasuura, H., Liu, Y., Lin, YL. (eds) Smart Sensors and Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-33201-7_18

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  • DOI: https://doi.org/10.1007/978-3-319-33201-7_18

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  • Online ISBN: 978-3-319-33201-7

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