Morphograms: exploiting correlation patterns to efficiently identify clinically significant events in intensive care units

Abstract

In this paper, we present a simple technique that utilizes the cross correlations between ECG signals and an arterial blood pressure (ABP) signal for the purpose of assessing signal quality and detecting artifacts in the ABP signal. The technique was tested using cases from a physician-annotated patient monitoring signal database from Beth Israel/Harvard-MIT University data bank. The results were encouraging: 45% of the manually annotated artifacts were correctly classified and 98% of the manually annotated true events were correctly classified.