• DocumentCode
    139650
  • Title

    A multi-parameters fusion model for non-invasive detection of intracranial pressure

  • Author

    Zhong Ji ; Xu Liu

  • Author_Institution
    Bioengeering Coll., Chongqing Univ., Chongqing, China
  • fYear
    2014
  • fDate
    26-30 Aug. 2014
  • Firstpage
    1743
  • Lastpage
    1746
  • Abstract
    On the basis of discussing the limitation of a single intracranial pressure non-invasive detection method in clinical application, the feasibility of the measurement and analysis model is investigated based on multi-parameters organic integration facing to intracranial pressure non-invasive measurement. Then the sensitivity analysis for the relation between the detected parameters and the change of intracranial pressure will be done. Finally, a synthesized non-invasive evaluation frame for intracranial pressure measurement with disease-adaptive model choice will be realized. By this way, a new idea is provided for the realization of the non-invasive measurement of intracranial pressure and its clinical application, which will be of significance for improving the clinical feasibility and monitoring accuracy of intracranial pressure non-invasive measuring methods.
  • Keywords
    blood pressure measurement; brain; medical signal detection; patient monitoring; physiological models; sensitivity analysis; sensor fusion; analysis model; clinical application; clinical feasibility; disease-adaptive model choice; intracranial pressure measurement; intracranial pressure noninvasive measurement; monitoring accuracy; multiparameter fusion model; multiparameter organic integration; noninvasive evaluation frame; sensitivity analysis; single intracranial pressure noninvasive detection method; Analytical models; Biological system modeling; Biomedical monitoring; Iterative closest point algorithm; Monitoring; Pathology; Pressure measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
  • Conference_Location
    Chicago, IL
  • ISSN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/EMBC.2014.6943945
  • Filename
    6943945