• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to previous page

Planning measures against disasters based on biosignal data from cardiac implantable device remote monitoring

Research Project

Project/Area Number 26461094
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Cardiovascular medicine
Research InstitutionFujita Health University

Principal Investigator

Watanabe Eiichi  藤田保健衛生大学, 医学部, 教授 (80343656)

Co-Investigator(Kenkyū-buntansha) 祖父江 嘉洋  藤田保健衛生大学, 医学部, 講師 (20724793)
清野 健  大阪大学, 基礎工学研究科, 准教授 (40434071)
原田 将英  藤田保健衛生大学, 医学部, 講師 (70514800)
Project Period (FY) 2014-04-01 – 2017-03-31
Project Status Completed (Fiscal Year 2016)
Budget Amount *help
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2015: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2014: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Keywords生体信号解析 / 心臓植込み型デバイス / 心不全 / 不整脈死 / 遠隔モニタリング / 災害 / 心肺停止 / 心拍数 / 呼吸数 / 心拍変動 / 心臓植え込み型デバイス / 不整脈 / 心臓 / 除細動 / 震災 / ストレス応答
Outline of Final Research Achievements

Patients with cardiac implantable devices are highly likely to have heart failure or sudden death at the time of a disaster. Cardiac implantable devices record data on the device status and biological signals such as heart beats and respirations, so that the details before and after the disaster can be examined by remote monitoring. The applicants have developed novel trend analysis methods for the heartbeats and respirations. By conducting a survey on the correlation between the biosignal trend analysis and outcome before and after the disaster in our hospital and affected areas, the risk of an occurrence of cardiac accidents is high for 3 weeks after the disaster, as reported. For this reason, we propose to confirm heart failure and arrhythmias by, for example, identifying cardiac implantable device cases and extracting the biosignal data in the device at the evacuation centers, by staff members such as the medical staff or Disaster Dispatch Medical Team.

Report

(4 results)
  • 2016 Annual Research Report   Final Research Report ( PDF )
  • 2015 Research-status Report
  • 2014 Research-status Report
  • Research Products

    (4 results)

All 2017 2015

All Journal Article (3 results) (of which Int'l Joint Research: 1 results,  Peer Reviewed: 3 results,  Acknowledgement Compliant: 3 results,  Open Access: 1 results) Presentation (1 results)

  • [Journal Article] Prognostic importance of novel oxygen desaturation metrics in patients with heart failure and central sleep apnea.2017

    • Author(s)
      Watanabe, E., Kiyono, K., Matsui, S., Somers, V. K., Sano, K.,Hayano, J., Ichikawa, T., Kawai, M., Harada, M., Ozaki, Y.
    • Journal Title

      J Card Fail

      Volume: 23 Issue: 2 Pages: 131-137

    • DOI

      10.1016/j.cardfail.2016.09.004

    • Related Report
      2016 Annual Research Report
    • Peer Reviewed / Int'l Joint Research / Acknowledgement Compliant
  • [Journal Article] Multiscale Entropy of the Heart Rate Variability for the Prediction of an Ischemic Stroke in Patients with Permanent Atrial Fibrillation2015

    • Author(s)
      Eiichi Watanabe, Ken Kiyono, Junichiro Hayano, Yoshiharu Yamamoto, Joji Inamasu, Mayumi Yamamoto, Tomohide Ichikawa, Yoshihiro Sobue, Masehide Harada, Yukio Ozaki
    • Journal Title

      PLoS ONE

      Volume: 10 Issue: 9 Pages: e0137144-e0137144

    • DOI

      10.1371/journal.pone.0137144

    • Related Report
      2015 Research-status Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Journal Article] Beat-to-beat T-wave amplitude variability in the2015

    • Author(s)
      Tomohide Ichikawa et al.
    • Journal Title

      Europace

      Volume: 未定 Issue: 1 Pages: 138-145

    • DOI

      10.1093/europace/euu404

    • Related Report
      2014 Research-status Report
    • Peer Reviewed / Acknowledgement Compliant
  • [Presentation] Improved prognostic assessment of heart failure patients using a machine learning technique incorporating heart rate variability parameters2017

    • Author(s)
      Watanabe E, Kiyono K, Ozaki Y.
    • Organizer
      第81回日本循環器学会学術集会
    • Place of Presentation
      石川県金沢市 石川県立音楽堂
    • Year and Date
      2017-03-17
    • Related Report
      2016 Annual Research Report

URL: 

Published: 2014-04-04   Modified: 2018-03-22  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi