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

Development of a noninvasive monitoring intracranial pressure by deep learning methods used the external auditory canal pressure pulse information

Research Project

Project/Area Number 18K08940
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 56010:Neurosurgery-related
Research InstitutionShinshu University

Principal Investigator

Furihata Kenji  信州大学, 医学部, 特任准教授 (90021013)

Co-Investigator(Kenkyū-buntansha) 本郷 一博  信州大学, 医学部附属病院, 特任教授 (00135154)
後藤 哲哉  信州大学, 医学部, 特任准教授 (30362130)
Project Period (FY) 2018-04-01 – 2023-03-31
Project Status Completed (Fiscal Year 2022)
Budget Amount *help
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2020: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2019: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Keywords頭蓋内圧 / 外耳道内圧脈波 / 深層学習 / 頭蓋内自然共振周波数 / 非侵襲的頭蓋内圧推定法 / パワースペクトル / 微分法によるピーク定量化 / 回帰木モデル / 非侵襲的頭蓋内圧モニタ / 機械学習 / 頭蓋内共振現象 / 脳圧亢進症状 / アンサンブル平均1パルス脈波 / 自発呼吸器変動 / LPC分析合成法 / 頸動脈脈波 / 脳の固有共振周波数 / 脳脊髄液 / 蝸牛水管 / 内耳 / 非侵襲的頭蓋内圧測定 / 頭蓋内共振系 / 音響圧センサ / 非侵襲モニタ / 深層学習法 / 多層パーセプトロン
Outline of Final Research Achievements

We found that the intracranial natural resonance frequency (NRF) depended only on the intracranial pressure (ICP) and that the relationship between the ICP and the NRF in the brain was able to be calculated using a quadratic function (ICP = 0.0329NRF*NRF + 0.0842NRF), with an excellent correlation (R2 = 0.9952). Therefore,the individual NRF depends only on the ICP value.Deep learning is effective for countermeasures against artifacts other than the extra-auditory canal pressure waveform (EACPW). These results confirmed that the predicted response using a regression tree model was the most stable and could be applied to new clinical data.

Academic Significance and Societal Importance of the Research Achievements

学術的意義は、頭蓋内の直流成分であるICP値と交流脈波信号EACPに含まれるNRF値の関係を解明したことである。
社会的意義は、深層学習法がEACP信号以外の雑音対策に有効であり、NRFを推定するにも回帰木モデルが新規データにも有効であることから、緊急医療現場でも精度よくICP値が類推できる点である。

Report

(6 results)
  • 2022 Annual Research Report   Final Research Report ( PDF )
  • 2021 Research-status Report
  • 2020 Research-status Report
  • 2019 Research-status Report
  • 2018 Research-status Report
  • Research Products

    (5 results)

All 2021 2020 2019 2018

All Journal Article (1 results) (of which Peer Reviewed: 1 results,  Open Access: 1 results) Presentation (3 results) Patent(Industrial Property Rights) (1 results)

  • [Journal Article] Natural resonance frequency of the brain depends on only intracranial pressure: clinical research2020

    • Author(s)
      Tetsuya Goto, Kenji Furihata and Kazuhiro Hongo
    • Journal Title

      Scientific Reports nature research

      Volume: 10-2526 Issue: 1 Pages: 1-10

    • DOI

      10.1038/s41598-020-59376-7

    • Related Report
      2019 Research-status Report
    • Peer Reviewed / Open Access
  • [Presentation] 非侵襲頭蓋内圧類推への挑戦2021

    • Author(s)
      後藤哲哉, 田中雄一郎, 降旗建治, 本郷一博
    • Organizer
      第30回脳神経外科手術と機器学会(CNTT2021)
    • Related Report
      2021 Research-status Report
  • [Presentation] 脳の血流による共振周波数は頭蓋内圧にのみ依存する:臨床研究2019

    • Author(s)
      後藤 哲哉、降旗 建治、本郷 一博
    • Organizer
      第58回 日本生体医工学会大会 PO-B-085
    • Related Report
      2019 Research-status Report
  • [Presentation] 非侵襲的頭蓋内圧測定への挑戦2018

    • Author(s)
      後藤哲哉、降旗建治、本郷一博、小池徳男、安本智志、前多宏信
    • Organizer
      日本脳神経外科学会第77回学術総会
    • Related Report
      2018 Research-status Report
  • [Patent(Industrial Property Rights)] 頭蓋内圧推定方法及び頭蓋内圧推定装置2019

    • Inventor(s)
      小池徳男、安本智志、本郷一博、後藤哲哉、降旗建治
    • Industrial Property Rights Holder
      小池徳男、安本智志、本郷一博、後藤哲哉、降旗建治
    • Industrial Property Rights Type
      特許
    • Filing Date
      2019
    • Related Report
      2018 Research-status Report

URL: 

Published: 2018-04-23   Modified: 2024-01-30  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi