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A time advance estimation method for human motions using stochastic resonance and multiple EMG sensors

Research Project

Project/Area Number 18K04071
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 20020:Robotics and intelligent system-related
Research InstitutionOita University (2019-2023)
Sasebo National College of Technology (2018)

Principal Investigator

Sadahiro Teruyoshi  大分大学, 理工学部, 准教授 (40424676)

Project Period (FY) 2018-04-01 – 2024-03-31
Project Status Completed (Fiscal Year 2023)
Budget Amount *help
¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2020: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2019: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Keywordsマルチセンサ / 確率共振 / 筋電位 / 電気力学的遅延 / 特徴量抽出 / 操作能力熟達 / EMG / EMD / 信号分解 / 粗く量子化された信号 / 機械学習 / 同定 / 事前推定 / 並列加算ネットワーク / マン・マシン・インターフェース / 人間動作推定 / 表面筋電位
Outline of Final Research Achievements

Electromyography can be an efficient transmission signals of human intentions to machines when it is used as input signal to machines. In conventional researches, the time lag from the occurrence of electromyography to the actual human joint movement , it is called as the electromechanical delay (EMD), has been ignored. Therefore, The low pass filter are widely used as a preprocess for the electromyography, although it makes EMD shorter by its phase lag phenomenon. In this study, we has proposed a preprocessing method using the stochastic resonance and multi-sensors, it does not make EMD shorter. By combining some estimation models, methods to estimate human movements in advance of the EMD, it is approximately 100 to 200 ms, are proposed and experimentally validated for their usefulness.

Academic Significance and Societal Importance of the Research Achievements

先行研究として EMD に着目し人間の運動の事前推定を行う研究を行ってはいたものの類似する研究はなく、そのような研究の発展として行われた。応募時に目的とした提案手法については実験的に検証を行うことができた。また研究を進めるにつれて、問題解決の糸口は入力の前処理をどのように行うかという観点と、推定モデルの選択にあることがわかった。そのため、提案手法以外にも2つの入力の前処理法と、3つの推定モデルを利用する方法を提案し、より事前に運動推定が可能で推定精度の良い手法の提案をおこなった。これら提案手法は、ますます重要になる VR 空間における視線移動時のVR酔い低減等に利用可能である。

Report

(7 results)
  • 2023 Annual Research Report   Final Research Report ( PDF )
  • 2022 Research-status Report
  • 2021 Research-status Report
  • 2020 Research-status Report
  • 2019 Research-status Report
  • 2018 Research-status Report
  • Research Products

    (17 results)

All 2023 2022 2021 2020 2019 Other

All Journal Article (1 results) (of which Peer Reviewed: 1 results,  Open Access: 1 results) Presentation (15 results) (of which Int'l Joint Research: 5 results) Remarks (1 results)

  • [Journal Article] A human motion angle prediction method using a neural network and feature-extraction-processed sEMG obtained in real time to utilize mechanical delay of sEMG2023

    • Author(s)
      Ikeda Naoki、Sadahiro Teruyoshi
    • Journal Title

      Journal of Advanced Simulation in Science and Engineering

      Volume: 10 Issue: 1 Pages: 102-115

    • DOI

      10.15748/jasse.10.102

    • ISSN
      2188-5303
    • Related Report
      2023 Annual Research Report 2022 Research-status Report
    • Peer Reviewed / Open Access
  • [Presentation] A Human Motion Angle Prediction Method using Whitening and Feature-Extraction for Multi-channel sEMG2023

    • Author(s)
      T.Sadahiro and N. Ikeda
    • Organizer
      62nd Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE)
    • Related Report
      2023 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 筋電位信号を入力とする Mixture of Experts によって EMD の変動を 考慮した肘関節角度の事前推定法の実験的検証2023

    • Author(s)
      岩本輝 , 貞弘晃宜
    • Organizer
      日本機械学会九州支部九州学生会第 54 回 学生員卒業研究発表講演会
    • Related Report
      2022 Research-status Report
  • [Presentation] An Elbow joint angle prediction method using a NN cosidering EMD with FE processed sEMG as inputs2022

    • Author(s)
      N. Ikeda and T.Sadahiro
    • Organizer
      The 41th JSST Annual International Conference on Simulation Technology
    • Related Report
      2022 Research-status Report
    • Int'l Joint Research
  • [Presentation] Elbow Joint Angle Estimation Method Using 1D-CNN with Quantized EMG Generated by SR and Multi-sensor2021

    • Author(s)
      D. Kashimoto and T. Sadahiro
    • Organizer
      The 40th JSST Annual Inter- national Conference on Simulation Technology
    • Related Report
      2021 Research-status Report
    • Int'l Joint Research
  • [Presentation] Elbow Joint Angle Estimation from Smoothed EMG Using Summing Network and Multi-sensor2021

    • Author(s)
      N. Ikeda and T. Sadahiro
    • Organizer
      The 40th JSST Annual Inter- national Conference on Simulation Technology
    • Related Report
      2021 Research-status Report
    • Int'l Joint Research
  • [Presentation] 並列加算ネットワークとマルチセンサを用いたローパスレス筋電位による肘関節角度推定法2021

    • Author(s)
      池田直樹、貞弘晃宜
    • Organizer
      日本機械学会九州支部九州学生会第52回学生員卒業研究発表講演会
    • Related Report
      2020 Research-status Report
  • [Presentation] First Person Shooter ゲームにおけるマウス操作時の筋電位測定によるニューラルネットワークを使用した熟達課程の解析2021

    • Author(s)
      平野遼太、貞弘晃宜
    • Organizer
      日本機械学会九州支部九州学生会第52回学生員卒業研究発表講演会
    • Related Report
      2020 Research-status Report
  • [Presentation] 粗く量子化された筋電位を用いた簡易な投球動作における熟達課程の解析2020

    • Author(s)
      宇野龍市、平野遼太、貞弘晃宜
    • Organizer
      第63回自動制御連合講演会
    • Related Report
      2020 Research-status Report
  • [Presentation] ヒステリシス関数とセンサ数の差異による確率共振によって粗く量子化された筋電位信号からの肘関節角度推定結果の比較2020

    • Author(s)
      柏本大知、貞弘晃宜
    • Organizer
      第39回計測自動制御学会九州支部学術講演会
    • Related Report
      2020 Research-status Report
  • [Presentation] 機械学習を用いた簡易な投球動作の熟達度判別2020

    • Author(s)
      宇野龍市、貞弘晃宜
    • Organizer
      日本機械学会九州支部九州学生会第51回学生員卒業研究発表講演会
    • Related Report
      2019 Research-status Report
  • [Presentation] 簡易な動作における粗く量子化された筋電位信号からの関節角度推定2020

    • Author(s)
      柏本大知、貞弘晃宜
    • Organizer
      日本機械学会九州支部九州学生会第51回学生員卒業研究発表講演会
    • Related Report
      2019 Research-status Report
  • [Presentation] マルチセンサと確率共振を用いた電気力学的遅延を拡大する筋電位信号の取得法2019

    • Author(s)
      貞弘晃宜、濱崎由光、古川徹
    • Organizer
      第62回自動制御連合講演会
    • Related Report
      2019 Research-status Report
  • [Presentation] Experimental Verification of Obtaining Longer EMD of EMG Using Multi-sensor and SR Phenomenon2019

    • Author(s)
      Teruyoshi Sadahiro, Yumi Hamasaki, Toru Furukawa
    • Organizer
      The 38th JSST Annual International Conference on Simulation Technology
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research
  • [Presentation] マルチセンサと確率共振を用いた筋電位からの関節角度推定2019

    • Author(s)
      濱崎 由光, 古川徹, 貞弘晃宜, 中浦茂樹
    • Organizer
      日本機械学会九州支部九州学生会第50回学生員卒業研究発表後援会
    • Related Report
      2018 Research-status Report
  • [Presentation] 深層学習による筋電位から関節角度までのモデル同定2019

    • Author(s)
      廣川 虎太朗, 中尾好宏, 貞弘晃宜, 中浦茂樹
    • Organizer
      日本機械学会九州支部九州学生会第50回学生員卒業研究発表後援会
    • Related Report
      2018 Research-status Report
  • [Remarks] イノベーション・ジャパン2021 シーズ展示(理工学部 貞弘 晃宜 准教授)

    • URL

      https://www.youtube.com/watch?v=7v_BCnRBV_U

    • Related Report
      2021 Research-status Report

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Published: 2018-04-23   Modified: 2025-01-30  

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