title: A systematic study of linear dynamic modeling of intracranial pressure dynamics.
abstract: Our group has proposed a generic time series data mining framework and demonstrated its potential as a noninvasive intracranial pressure (ICP) assessment approach. The linear dynamic model (LDM) was used in our previous work without rigorous justification. In the current study, we performed a systematic study of the practical performance of the LDM for ICP dynamics by investigating three important aspects to consider in using the LDM to model ICP dynamics. Those three aspects include the fitness of the LDM to data, the generalizability of the models, and the choice of input signals to the models. Our study results show that the fitness of the LDM to data is excellent and the LDM for ICP dynamics is well generalizable, which is of particular interest to adopting our time series data mining framework for noninvasive ICP assessment.
authors.affiliation: Neural Systems and Dynamics Lab, Department of Neurosurgery, David Geffen School of Medicine at University of California, Los Angeles, CA 90095, USA. KSunghan@mednet.ucla.edu
authors.forename: Sunghan
authors.initials: S
authors.lastname: Kim
authors.forename: Marvin
authors.initials: M
authors.lastname: Bergsneider
authors.forename: Xiao
authors.initials: X
authors.lastname: Hu
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D007427:Intracranial Pressure / Q000502:physiology*; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult