• DocumentCode
    380911
  • Title

    Adaptive approach for change detection in EMG recordings

  • Author

    El Falou, W. ; Khalil, M. ; Duchêne, J.

  • Author_Institution
    Fac. of Eng. I, Lebanese Univ., Tripoli, Lebanon
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    1875
  • Abstract
    In this paper we present a new algorithm to detect abrupt changes in a signal when there is no a priori knowledge of the hypotheses on the process to be detected. This algorithm is based on the CUSUM algorithm. It can be applied in case of frequency and energy changes. This algorithm works when the samples are dependent and autoregressive modeling is needed. It is used to distinguish EMG segments from noise segments.
  • Keywords
    adaptive signal detection; autoregressive processes; electromyography; medical signal detection; noise; CUSUM algorithm; EMG recordings; EMG segments; a priori knowledge; adaptive approach; autoregressive modeling; change detection; energy changes; frequency changes; likelihood ratio; noise segments; Biomedical signal processing; Change detection algorithms; Electromyography; Event detection; Frequency; Knowledge engineering; Probability density function; Signal processing; Signal processing algorithms; Signal to noise ratio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Print_ISBN
    0-7803-7211-5
  • Type

    conf

  • DOI
    10.1109/IEMBS.2001.1020591
  • Filename
    1020591