Model-based analysis of sEMG signals using Stockwell transform features under varied muscle fiber composition and conduction velocity.

Detalles Bibliográficos
Publicado en:Medical & Biological Engineering & Computing Vol. 63; no. 11; pp. 3381 - 3399
Autores principales: G., Venugopal, N., Sidharth, Karthick, P. A.
Formato: Journal Article
Publicado: Springer Nature Nov2025
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=189590717&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 189590717
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        01400118
        PO0
      jtl: Medical & Biological Engineering & Computing
      issn: 01400118
      maglogo: N
    pubinfo:
      dt: Nov2025
      vid: 63
      iid: 11
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        189590717
        186358787
        10.1007/s11517-025-03403-0
        189590717
      ppf: 3381
      ppct: 18
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
      tig:
        atl: Model-based analysis of sEMG signals using Stockwell transform features under varied muscle fiber composition and conduction velocity.
      aug:
        au:
          G., Venugopal
          N., Sidharth
          Karthick, P. A.
        affil: https://ror.org/04yn30r61 Department of Instrumentation and Control Engineering, N.S.S. College of Engineering (Affiliated to APJ Abdul Kalam Technological University, Kerala, India), Palakkad, Kerala, India
      sug:
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
      ab:
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N