Title :
Morphograms: exploiting correlation patterns to efficiently identify clinically significant events in intensive care units
Author :
AIi, W. ; Eshelman, Larry
Author_Institution :
Philips Res., Briarcliff Manor, NY, USA
Abstract :
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.
Keywords :
correlation methods; electrocardiography; haemodynamics; medical signal detection; medical signal processing; patient monitoring; signal classification; ECG; arterial blood pressure; artifact detection; clinically significant events; intensive care units; morphograms; physician-annotated patient monitoring signal database; Condition monitoring; Electrocardiography; Event detection; Heart beat; Morphology; Patient monitoring; Shape; ABP; ECG; hemodynamic;
Conference_Titel :
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-8439-3
DOI :
10.1109/IEMBS.2004.1403217