Automatic identification of intracranial pressure waveform during external ventricular drainage clamping: segmentation via wavelet analysis.

ABSTRACT: Objective. The objective of this study is to develop and validate a method for automatically identifying segments of intracranial pressure (ICP) waveform data from external ventricular drainage (EVD) recordings during intermittent drainage and closure.Methods. The proposed method uses time-frequency analysis through wavelets to distinguish periods of ICP waveform in EVD data. By comparing the frequency compositions of the ICP signals (when the EVD system is clamped) and the artifacts (when the system is open), the algorithm can detect short, uninterrupted segments of ICP waveform from the longer periods of non-measurement data. The method involves applying a wavelet transform, calculating the absolute power in a specific range, using Otsu thresholding to automatically identif

SUBMITTER: Megjhani M 

PROVIDER: S-EPMC10403046 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature