• DocumentCode
    3481427
  • Title

    Detection of EEG basic rhythm feature by using band relative intensity ratio (BRIR)

  • Author

    Ji, Zhong ; Qin, Shuren

  • Author_Institution
    Test center, Chongqing Univ., China
  • Volume
    6
  • fYear
    2003
  • fDate
    6-10 April 2003
  • Abstract
    In the clinical analysis and processing for EEG, because of the difference of ages and pathology, it is possible for abnormal waves to appear, related with pathology. Also, the restraint of normal rhythms could be abnormal. But at present doctors estimate if a certain rhythm is restrained only by eye or by some simple analysis methods in clinical EEG detection, which will inevitably lead to some errors and are not observable. By "the virtual EEG record and analysis instrument" introduced in this paper, all kinds of characteristic waveforms (e.g. epileptic wave and spikes wave etc.) can be detected and analyzed in time-frequency domain. From the view of clinical application, the concept of band relative intensity ratio (BRIR) is introduced with time-frequency domain analysis, by the use of which we can obtain the relative intensity of all basic rhythms in a certain time period, and this is believed to provide a good assisting analysis method.
  • Keywords
    electroencephalography; feature extraction; medical signal detection; time-frequency analysis; BRIR; EEG detection; abnormal waves; band relative intensity ratio; basic rhythm feature; clinical analysis; epileptic wave; spikes; time-frequency domain analysis; virtual EEG record and analysis instrument; Brain; Electroencephalography; Frequency domain analysis; Instruments; Pathology; Pediatrics; Rhythm; Signal resolution; Sleep; Time frequency analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-7663-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.2003.1201710
  • Filename
    1201710