Bayesian tracking of intracranial pressure signal morphology

摘要

BackgroundThe waveform morphology of intracranial pressure (ICP) pulses holds essential informations about intracranial and cerebrovascular pathophysiological variations. Most of current ICP pulse analysis frameworks process each pulse independently and therefore do not exploit the temporal dependency existing between successive pulses. We propose a probabilistic framework that exploits this temporal dependency to track ICP waveform morphology in terms of its three peaks.