Reduction of false blood pressure alarms by use of electrocardiogram blood pressure relationships

This paper presents an algorithm for reducing false alarms related to changes in arterial blood pressure (ABP) in intensive care unit (ICU) monitoring. The algorithm assesses the ABP signal quality, analyzes the ECG-ABP relationships using a fuzzy logic approach, and post-processes (accepts or rejects) ABP alarms produced by a commercial monitor. The algorithm was developed and evaluated using disjoint sets of data from the MIMIC database. By rejecting 96.8% of the false ABP alarms (182 of 188) produced by the monitor using the test set of data, the algorithm was able to reduce the false alarm rate from 34.9% to 1.7% of ABP alarms while accepting 99.4% of true ABP alarms (346 of 348). The results show that the algorithm is both effective and practical, and feasible for use in future monitoring systems