• DocumentCode
    6937
  • Title

    A New Approach for Investigating Intracranial Pressure Signal: Filtering and Morphological Features Extraction from Continuous Recording

  • Author

    Calisto, A. ; Galeano, M. ; Serrano, S. ; Calisto, A. ; Azzerboni, Bruno

  • Author_Institution
    Dept. of Electron. Eng., Ind. Chem. & Eng., Univ. of Messina, Messina, Italy
  • Volume
    60
  • Issue
    3
  • fYear
    2013
  • fDate
    Mar-13
  • Firstpage
    830
  • Lastpage
    837
  • Abstract
    Nowadays, the Intracranial Pressure (ICP) monitoring has become the most common method of investigation for both traumatic and chronic neural pathologies. ICP signals are typically triphasic, that is, in a single waveform, three subpeaks can be identified. This work outlines a new algorithm to identify subpeaks from the ICP recordings and to extract a number of 20 meaningful parameter trends. The validity of the implemented method has been proved through a comparison between the automatic subpeaks identification by the algorithm and the manually marked subpeaks by a neurosurgeon. The automatic marking system has identified subpeaks for the 63.74% (mean value) of pulse waves, providing the position and amplitude of each identified subpeak within a tolerance of ±7 samples. This automatic system provides a feature set to be used by classification software to obtain more precise and easier diagnosis in all those cases that involve brain damages or diseases.
  • Keywords
    brain; classification; diseases; feature extraction; medical signal processing; neurophysiology; patient diagnosis; patient monitoring; ICP recordings; ICP signals; automatic subpeak identification; automatic system; brain damages; chronic neural pathologies; classification software; continuous recording; diseases; filtering features extraction; intracranial pressure monitoring; intracranial pressure signal; morphological features extraction; neurosurgeon; patient diagnosis; pulse wave mean value; single waveform; subpeak amplitude; subpeak position; traumatic pathologies; triphasic signal; Feature extraction; Filtering algorithms; Finite impulse response filter; Iterative closest point algorithm; Noise; Signal processing algorithms; Biomedical monitoring; Computer aided diagnosis; Hypertension; Intracranial pressure (ICP) sensors; Medical signal detection; signal processing; transducers; Adult; Aged; Algorithms; Diagnosis, Computer-Assisted; Female; Humans; Hydrocephalus, Normal Pressure; Intracranial Pressure; Male; Middle Aged; Monitoring, Physiologic; Reproducibility of Results; Signal Processing, Computer-Assisted; Spinal Puncture; Transducers;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2012.2191550
  • Filename
    6172560