Single wave extraction in continuous intracranial pressure signal with lifting wavelet transformation and discrimination rules

Objective: This article describes a novel method for processing continuous intracranial pressure (ICP) signals with lifting wavelet transformation and discrimination rules for ICP waveform morphology. Methods: First, lifting wavelet was applied to detect the extreme points of ICP waveform preliminarily; then, the extreme points that were undetected or falsely detected are determined by using the discrimination rules repeatedly; finally, those falsely detected and undetected points were removed or corrected to improve the accuracy of identified individual pulse. Results: The algorithm was employed to analyze continuous ICP signals of nine patients. Signals were recorded for 30 min each. Each signal was divided into 30-s segments and analyzed. The accuracy rate of 98.58% was obtained. Conclusion: The method described in this article has given a possibility for the clinical use of ICP waveform. By identifying the single ICP wave effectively, not only mean ICP but also single ICP wave amplitude and latency can be computed precisely with this new method.