• DocumentCode
    2099451
  • Title

    Utilization of temporal information for intracranial pressure development trend forecasting in traumatic brain injury

  • Author

    Mengling Feng ; Zhuo Zhang ; Cuntai Guan ; Hardoon, D.R. ; King, N.K.K. ; Boon Chuan Pang ; Beng Ti Ang

  • Author_Institution
    Inst. for Infocomm Res., Singapore, Singapore
  • fYear
    2012
  • fDate
    Aug. 28 2012-Sept. 1 2012
  • Firstpage
    3930
  • Lastpage
    3934
  • Abstract
    Objective. Our primary objective is to demonstrate and statistically justify that forecasting models that utilize temporal information of the historical readings of ICP and related parameters are superior, in terms of performance, compared with models that do not make use of temporal information. Material & Method. 82 traumatic brain injuries patients, who were admitted between 2002 to 2007 and were continuously monitored on ICP for more than 24 hours, are selected for the study. Together with ICP, MAP and PbtO2 were also monitored, and PRx was calculated as a moving correlation between ICP and MAP. The development trends of ICP and the related parameters are measured by first segmenting the time-series data into multiple periodic windows. The development trend of each periodic window is then discretized into three classes - elevate, stay or reduce - based on the concept of “trend line”. A systematic framework is developed to compare the forecast performance between the temporal and non-temporal models. Findings. Experimental results demonstrate that the utilization of temporal information directly leads to a considerable boost in trend forecasting performance (on average 20% relative performance gain was achieved). Moreover, the performance gain is confirmed to be statistically significant (p-value <; 0.0001) based on a paired t-test.
  • Keywords
    biomedical measurement; blood vessels; brain; forecasting theory; injuries; medical signal processing; patient monitoring; pressure measurement; statistical analysis; time series; ICP; MAP; PbtO2; brain tissue oxygenation; historical readings; intracranial pressure development trend forecasting model; mean arterial pressure; moving correlation; multiple periodic windows; nontemporal models; paired t-test; performance gain; pressure reactivity index; statistics; temporal information utilization; time-series data segmentation; traumatic brain injured patients; Forecasting; Iterative closest point algorithm; Machine learning algorithms; Market research; Monitoring; Predictive models; Vectors; Algorithms; Brain Injuries; Humans; Intracranial Pressure; Monitoring, Physiologic; Time Factors;
  • 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.2012.6346826
  • Filename
    6346826