• DocumentCode
    429080
  • Title

    A signal analysis algorithm for determining brain compliance non-invasively

  • Author

    Manwaring, P. ; Wichern, D. ; Manwaring, M. ; Manwaring, J. ; Manwaring, K.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Brigham Young Univ., Provo, UT, USA
  • Volume
    1
  • fYear
    2004
  • fDate
    1-5 Sept. 2004
  • Firstpage
    353
  • Lastpage
    356
  • Abstract
    Patients with increased intracranial pressure (ICP) caused by hydrocephalus or brain injury have poor brain compliance or increased brain stiffness. The condition is commonly treated by a surgical diversion of cerebrospinal fluid (CSF) through placement of a ventriculoperitoneal (VP) shunt. These inserted devices frequently fail and require replacement. Assessment of failed devices typically requires an invasive surgical procedure to implant an ICP sensor. Brain compliance can be determined non-invasively by comparing the intracranial pressure (ICP) waveform to the digital artery waveform. The ICP waveform is derived from a piezo sensor snugged into the external ear canal and worn as a headset. The digital artery waveform is derived from a stand pulse oximeter. Digital signal processing performed on sampled data from these two sensors shows a time-lag or phase relationship between the two waves which widens with worsening brain stiffness or compliance. An algorithm is presented that shows how these signals can be used to compute brain compliance. An instrument designed to calculate real-time brain compliance to aid healthcare professionals is described.
  • Keywords
    biomechanics; brain; elasticity; medical signal processing; oximetry; pressure sensors; brain injury; brain stiffness; cerebrospinal fluid; digital artery waveform; digital signal processing; external ear canal; hydrocephalus; increased intracranial pressure; piezo sensor; real-time brain compliance; signal analysis; stand pulse oximeter; ventriculoperitoneal shunt; Arteries; Brain injuries; Cranial pressure; Ear; Implants; Intracranial pressure sensors; Signal analysis; Signal processing algorithms; Surgery; Wearable sensors; Algorithm; Fast Fourier Transform; Fourier Transform; brain compliance; hydrocephalus; intracranial pressure; phase angle;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
  • Conference_Location
    San Francisco, CA
  • Print_ISBN
    0-7803-8439-3
  • Type

    conf

  • DOI
    10.1109/IEMBS.2004.1403165
  • Filename
    1403165