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2020 Fiscal Year Final Research Report

Development of adoptive nonlinear myoelectric signal detection technique for user-friendly man-machine interface

Research Project

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Project/Area Number 18H01487
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Review Section Basic Section 21060:Electron device and electronic equipment-related
Research InstitutionHokkaido University

Principal Investigator

Kasai Seiya  北海道大学, 量子集積エレクトロニクス研究センター, 教授 (30312383)

Project Period (FY) 2018-04-01 – 2021-03-31
Keywords筋電検出 / 非線形 / 感覚フィードバック
Outline of Final Research Achievements

In this study, we developed a user-friendly man-machine interface (MMI) that can detect the user's motion and intention using surface electric myosignal (EMS). The newly developed MMI includes the reduction of the error in the EMS detection and a MMI-integrable vibration haptic feedback device with rich expression. The EMS detection error was reduced by a self-parameter optimization mechanism in our unique nonlinear EMS detection technique, which could make the system adaptive to the user and the environment. We also showed an artificial haptic device integrating two small vibration motors that could generate a super-low frequency vibration down to 2.5 Hz by beating, which was two orders of magnitude smaller than that from single motor.

Free Research Field

半導体電子デバイス

Academic Significance and Societal Importance of the Research Achievements

本研究により、使用者の動きや意図を読み取る筋電検出に非線形工学を適用する独自手法により難点を克服する新しい技術を創り出した。また、振動をとおして使用者に情報伝達する人工感覚の情報量を大幅に増やす方法を開拓した。これらの成果は、直感的な操作を可能にする筋電型インターフェースの問題点を解決し「思い通り」の操作体験を提供できるようするものであり、操作手順が煩雑な種々の機器を使いやすくする技術につながる。

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Published: 2022-01-27  

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