• DocumentCode
    3405235
  • Title

    Characterization of changes in evoked potentials with applications to detection of possible impact acceleration injury

  • Author

    Prahlad, Meera ; Kong, Xuan ; Kaufman, Bernice ; Rog, Andre

  • Author_Institution
    Dept. of Electr. Eng., Northern Illinois Univ., DeKalb, IL, USA
  • fYear
    1996
  • fDate
    29-31 Mar 1996
  • Firstpage
    353
  • Lastpage
    356
  • Abstract
    Transient and time varying changes in neuroelectric signals, such as evoked potentials (EPs), have been widely used to quantify neurological system properties. Animal experiments have demonstrated a strong correlation between latency changes in EPs and head/neck injuries resulting from impact acceleration. Accurate and immediate detection of similar changes in human EPs is crucial to quantify the effects of impact acceleration on the safety and functioning of naval personnel. The robustness of the adaptive latency change detection/estimation algorithm is examined here to establish its usefulness for analyzing noisy and time varying EPs. The long term objective is to establish an impact injury threshold for properly restrained personnel
  • Keywords
    bioelectric potentials; biomechanics; impact (mechanical); medical signal processing; adaptive latency change detection/estimation algorithm; animal experiments; evoked potentials changes characterization; head/neck injuries; impact acceleration injury detection; impact injury threshold; naval personnel functioning; naval personnel safety; neuroelectric signals; properly restrained personnel; time varying changes; transient changes; Acceleration; Animals; Delay; Humans; Injuries; Neck; Personnel; Robustness; Safety; Time varying systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering Conference, 1996., Proceedings of the 1996 Fifteenth Southern
  • Conference_Location
    Dayton, OH
  • Print_ISBN
    0-7803-3131-1
  • Type

    conf

  • DOI
    10.1109/SBEC.1996.493223
  • Filename
    493223