Zong Wei, Nielsen Larry, Gross Brian, Brea Juan, Frassica Joseph
Patient Care and Monitoring Solutions, Philips Healthcare, Andover, MA, USA.
Physiol Meas. 2016 Aug;37(8):1355-69. doi: 10.1088/0967-3334/37/8/1355. Epub 2016 Jul 25.
There has been a high rate of false alarms for the critical electrocardiogram (ECG) arrhythmia events in intensive care units (ICUs), from which the 'crying-wolf' syndrome may be resulted and patient safety may be jeopardized. This article presents an algorithm to reduce false critical arrhythmia alarms using arterial blood pressure (ABP) and/or photoplethysmogram (PPG) waveform features. We established long duration reference alarm datasets which consist of 573 ICU waveform-alarm records (283 for development set and 290 for test set) with total length of 551 patent days. Each record has continuous recordings of ECGs, ABP and/or PPG signals and contains one or multiple critical ECG alarms. The average length of a record is 23 h. There are totally 2408 critical ECG alarms (1414 in the development set and 994 in the test set), each of which was manually annotated by experts. The algorithm extracts ABP/PPG pulse features on a beat-by-beat basis. For each pulse, five event feature indicators (EFIs), which correspond to the five critical ECG alarms, are generated. At the time of a critical ECG alarm, the corresponding EFI values of those ABP/PPG pulses around the alarm time are checked for adjudicating (accept/reject) this alarm. The algorithm retains all (100%) the true alarms and significantly reduces the false alarms. Our results suggest that the algorithm is effective and practical on account of its real-time dynamic processing mechanism and computational efficiency.
重症监护病房（ICU）中关键心电图（ECG）心律失常事件的误报率一直很高，这可能导致“狼来了”综合征，并危及患者安全。本文提出了一种利用动脉血压（ABP）和/或光电容积脉搏波（PPG）波形特征来减少关键心律失常误报的算法。我们建立了长时间的参考警报数据集，该数据集由573条ICU波形-警报记录（283条用于开发集，290条用于测试集）组成，总时长为551个患者日。每条记录都包含心电图、ABP和/或PPG信号的连续记录，并包含一个或多个关键心电图警报。一条记录的平均时长为23小时。共有2408个关键心电图警报（开发集中有1414个，测试集中有994个），每个警报均由专家手动标注。该算法逐搏提取ABP/PPG脉搏特征。对于每个脉搏，会生成五个与五个关键心电图警报相对应的事件特征指标（EFI）。在出现关键心电图警报时，检查警报时间前后那些ABP/PPG脉搏的相应EFI值，以判定（接受/拒绝）该警报。该算法保留了所有（100%）真实警报，并显著减少了误报。我们的结果表明，该算法因其实时动态处理机制和计算效率而有效且实用。
