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False Ventricular-Fibrillation/Flutter Alarm Reduction of Patient Monitoring Systems in Intensive Care Units

机译:重症监护病房患者监护系统的虚假心室颤动/扑动警报减少

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Generally in hospitals, false arrhythmia alarm rates are very high in intensive care units (ICUs) patient monitors 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 alarms being as high as 90%. Ventricular-fibrillation/flutter is the most commonly identified arrhythmia in cardiac arrest patients and it usually ends in death within minutes unless an urgent treatment is not applied. Therefore, in our study, we consider the alarms triggered by ventricular-flutter/fibrillation condition. This type of alarm is usually triggered by ECG and pulsatile waveforms recorded by monitoring equipments, which have standard alarm triggering criteria such as instantaneous thresholds on the predictor values. Most of the ventricular-fibrillation/flutter false 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 false ECG alarms in ICUs. Photoplethysmogram (PPG), arterial blood pressure (ABP) or both PPG and ABP can be used for this purpose. These waveforms are the least noisy pressure signals 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. Our best result is 100%/98.1% in terms of sensitivity/specificity based on the Cinc2015 Challenge training dataset.
机译:通常,在医院中,重症监护病房(ICU)病人监护仪的假性心律失常警报率非常高,而与它们的品牌和价格无关。这些错误发出的警报会扰乱患者的休息,浪费医院资源,并使医院工作人员对潜在的紧急情况不敏感,这被称为错误警报疲劳。据估计,床边监护仪发出的威胁生命的心电图(ECG)警报中有43%是错误的,某些类别的警报高达90%。室颤/颤动是心脏骤停患者中最常见的心律失常,除非不采取紧急治疗,否则通常会在几分钟内死亡。因此,在我们的研究中,我们考虑了由心室颤动/颤动情况触发的警报。这种类型的警报通常由监视设备记录的ECG和脉动波形触发,这些设备具有标准的警报触发标​​准,例如预测值的瞬时阈值。大多数心室纤颤/颤动错误警报是由单通道伪影引起的。在本研究中,我们旨在将ECG功能与来自其他独立信号的信息融合在一起,并获得针对ICU的更强大的警报算法。脉冲波形是高度相关的信号,可用于确认警报类别并抑制ICU中大量的错误ECG警报。光体积描记图(PPG),动脉血压(ABP)或PPG和ABP均可用于此目的。这些波形是某些ICU中可用的噪声最小的压力信号,并且很少包含与ECG相关的伪影。我们实现了四种不同的算法,这些算法使用了来自ECG,PPG和ABP波形的信息,并比较了结果。根据Cinc2015挑战训练数据集,在敏感性/特异性方面,我们的最佳结果是100 \%/ 98.1 \%。

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