DocumentCode
2484635
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
fYear
0
fDate
0-0 0
Firstpage
31
Lastpage
34
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 standard 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 is described
Keywords
blood pressure measurement; blood vessels; brain; ear; medical signal processing; oximetry; piezoelectric devices; brain injury; brain stiffness; cerebrospinal fluid; digital artery waveform; digital signal processing; external ear canal; hydrocephalus; increased intracranial pressure; noninvasive brain compliance determination; piezo sensor; pulse oximeter; signal analysis algorithm; 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
Computer Architectures for Machine Perception, 2003 IEEE International Workshop on
Conference_Location
Hong Kong
Print_ISBN
0-7803-8612-4
Type
conf
DOI
10.1109/ISSMD.2004.1689554
Filename
1689554
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