IDEAS home Printed from https://ideas.repec.org/a/taf/gcmbxx/v26y2023i16p2057-2069.html
   My bibliography  Save this article

Random forest-based simultaneous and proportional myoelectric control system for finger movements

Author

Listed:
  • Khairul Anam
  • Dwiretno Istiyadi Swasono
  • Agus Triono
  • Aris Z. Muttaqin
  • Faruq S. Hanggara

Abstract

A classification scheme for myoelectric control systems (MCS) cannot mimic complex hand movements. This paper presents simultaneous and proportional MCS by estimating the angles of fourteen finger joints using time-domain feature extraction and random forest. The experimental results show that the best feature was the root mean square (RMS). Furthermore, the random forest attained an average coefficient of determination (R2) of 0.85 compared to other regressors which perform below 0.75. The ANOVA tests indicated that the performance of the proposed system was significantly different. Therefore, the proposed system will be the best option for real-time MCS applications in the future.

Suggested Citation

  • Khairul Anam & Dwiretno Istiyadi Swasono & Agus Triono & Aris Z. Muttaqin & Faruq S. Hanggara, 2023. "Random forest-based simultaneous and proportional myoelectric control system for finger movements," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 26(16), pages 2057-2069, December.
    • Handle: RePEc:taf:gcmbxx:v:26:y:2023:i:16:p:2057-2069
    DOI: 10.1080/10255842.2023.2165068
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/10255842.2023.2165068
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/10255842.2023.2165068?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:gcmbxx:v:26:y:2023:i:16:p:2057-2069. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/gcmb .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.