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A Detailed Protocol for Physiological Parameters Acquisition and Analysis in Neurosurgical Critical Patients
Published on: October 17, 2017
A systematic study of linear dynamic modeling of intracranial pressure dynamics
Sunghan Kim1, Marvin Bergsneider, Xiao Hu
1Neural 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
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.
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