IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v45y2018i4p714-726.html
   My bibliography  Save this article

Adaptive threshold method for peak detection of surface electromyography signal from around shoulder muscles

Author

Listed:
  • Amanpreet Kaur
  • Ravinder Agarwal
  • Amod Kumar

Abstract

This paper illustrates the accurate identification of the surface electromyography signal obtained from the shoulder muscles (Teres, Trapezius and Pectoralis) of amputee subjects with three different arm motions (elevation, protraction and retraction). During the acquisition of the signal, a variety of variations (amplitude, frequency and noise) were introduced into the acquired signal which will misguide in the prediction of motion of the shoulder. Therefore, a novel approach has been aimed to adaptively adjust the threshold of Teager energy operator in order to filter the unwanted peaks in the pre-processing stage of the surface electromyography (SEMG) signal. Results show that the proposed approach is accurate and effective in the analysis of biomedical signal where peaks are important to detect without the knowledge of the shape of the waveform. As clinical research continues, these algorithms helps us to process SEMG signal and the identified signal would be used to design more accurate and efficient controllers for the upper-limb amputee.

Suggested Citation

  • Amanpreet Kaur & Ravinder Agarwal & Amod Kumar, 2018. "Adaptive threshold method for peak detection of surface electromyography signal from around shoulder muscles," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(4), pages 714-726, March.
  • Handle: RePEc:taf:japsta:v:45:y:2018:i:4:p:714-726
    DOI: 10.1080/02664763.2017.1293624
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2017.1293624
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/02664763.2017.1293624?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:japsta:v:45:y:2018:i:4:p:714-726. 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/CJAS20 .

    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.