• DocumentCode
    2073503
  • Title

    Extraction of stationary components in biosignal discrimination

  • Author

    Martinez-Vargas, J.D. ; Cardenas-Pena, D. ; Castellanos-Dominguez, German

  • Author_Institution
    Signal Process. & Recognition Group, Univ. Nac. de Colombia, Manizales, Colombia
  • fYear
    2012
  • fDate
    Aug. 28 2012-Sept. 1 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Biosignal recordings are widely used in the medical environment to support the evaluation and the diagnosis of pathologies. Nevertheless, the main difficulty lies in the non-stationary behavior of the biosignals, difficulting the obtention of patterns characterizing the changes in physiological or pathological states. Thus, the obtention of the stationary and non-stationary components of a biosignal is still an open issue. This work proposes a methodology to detect time-homogeneities based on time-frequency analysis with aim to extract the non-stationary behavior of the biosignal. Results show an increase in the stationarity and in the distance between classes of the reconstructions from the enhanced time-frequency representations. The stationary components extracted with the proposed approach can be used to solve biosignal classification problems.
  • Keywords
    diseases; feature extraction; medical signal processing; patient diagnosis; signal classification; signal reconstruction; signal representation; time-frequency analysis; biosignal classification problems; biosignal discrimination; biosignal recordings; enhanced time-frequency representations; medical environment; non-stationary components; nonstationary behavior; pathological states; pathology diagnosis; pattern obtention; physiological states; reconstructions; stationary component extraction; stationary obtention; time-frequency analysis; Databases; Electroencephalography; Heart rate variability; Stochastic processes; Time frequency analysis; Time series analysis; Multivariate locally stationary time series; Time-evolving Latent Variable Decomposition; Databases, Factual; Electroencephalography; Epilepsy; Female; Humans; Male; Models, Biological; Signal Processing, Computer-Assisted; Signal-To-Noise Ratio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4119-8
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/EMBC.2012.6345856
  • Filename
    6345856