Reducing false arrhythmia alarms of patient monitoring systems in intensive care units

Abstract

Generally in hospitals, intensive care units (ICUs) have high rates of arrhythmia alarms independent of their brands and prices. These falsely issued alarms disrupt patients' rest, drain hospital resources, and desensitize the hospital staff to potential emergency situations, which is named as false alarm fatigue. It has been estimated that 43% of life threatening electrocardiogram (ECG) alarms issued by bedside monitors are false, with some categories of alarm being as high as 90%. In our study, we consider the alarms triggered by four life threatening conditions. These alarms are usually triggered by ECG and pulsatile waveforms recorded by monitoring equipment, which have standard alarm triggering criteria such as instantaneous thresholds on the predictor values. Most of the ICU alarms are caused by single channel artifacts. In this study, we aim to fuse ECG features with information from other independent signals and get more robust alarm algorithms for ICUs. Pulsatile waveforms, which are highly correlated signals, can be used to corroborate the alarm category and to suppress significant number of ECG alarms in ICUs. Photoplethysmogram (PPG), arterial blood pressure (ABP) or both PPG and ABP can be used for this purpose. These waveformsare the least noisy pressure signal available in certain ICUs and rarely contain ECG-related artifacts. We implement four different algorithms that use information from ECG, PPG and ABP waveforms, and compare the results.