title: A signal analysis algorithm for determining brain compliance non-invasively.
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.
authors.affiliation: Dept. of Electr. & Comput. Eng., Brigham Young Univ., Provo, UT, USA.
authors.forename: P
authors.initials: P
authors.lastname: Manwaring
authors.forename: D
authors.initials: D
authors.lastname: Wichern
authors.forename: M
authors.initials: M
authors.lastname: Manwaring
authors.forename: J
authors.initials: J
authors.lastname: Manwaring
authors.forename: K
authors.initials: K
authors.lastname: Manwaring