Optimizing cardiac resuscitation outcomes using wavelet analysis
Optimizing cardiac resuscitation outcomes using wavelet analysis
复制标题
使用小波分析优化心脏复苏结果
DOI：
10.1109/iembs.2009.5332509
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
K. Nanthakumar
中科院分区：
文献类型：
--
作者：
K. Umapathy;S. Krishnan;Stéphane Massé;Xudong Hu;Paul Dorian;K. Nanthakumar
心室颤动（VF）是最致命的心律失常，如果在其发生后几分钟内未经治疗，会导致心脏性猝死。使用电击的除颤将心脏复位到自主循环（ROSC）状态，然而其成功取决于各种因素，例如心肌的存活性和VF发作到除颤之间的时间滞后。最近的研究报告称，在实施电击之前进行心肺复苏（CPR）程序可以提高生存率，尤其是当VF未得到治疗超过5分钟时。考虑到VF必须在有限的时间内进行治疗以获得更好的生存率，选择正确的治疗（休克参数，先休克或先CPR，药物管理）至关重要。在帮助这种选择时，如果能够以接近实时的速率提供关于VF特征及其与电击结果的关系的客观反馈，则对于急救医务人员（EMS）将是巨大的帮助。文献中的现有工作已经证明了VF波形的特征与除颤的结果（ROSC）之间的相关性。拟议的工作改进了这一点，试图达到一个近乎实时的监测工具，以帮助EMS工作人员。使用从16头猪VF期间收集的数据，所提出的小波方法在成功预测电击结果方面达到了94%的总体准确度。
Ventricular fibrillation (VF) is the most lethal of cardiac arrhythmias that leads to sudden cardiac death if untreated within minutes of its occurrence. Defibrillation using electric shock resets the heart to return to spontaneous circulation (ROSC) state, however the success of which depends on various factors such as the viability of myocardium and the time lag between the onset of VF to defibrillation. Recent studies have reported that performing cardio pulmonary resuscitation (CPR) procedure prior to applying shock increases the survival rate especially when VF is untreated for more than 5 minutes. Considering the limited time within which the VF has to be treated for better survival rates, the choice of the right therapy (shock parameters, shock first or CPR first, drug administration) is vital. In aiding this choice, it would be of immense help for emergency medical staff (EMS) if an objective feedback could be provided at near real-time rate on the VF characteristics and its relation to the shock outcomes. Existing works in the literature have demonstrated correlation between the characteristics of the VF waveform and the outcome (ROSC) of the defibrillation. The proposed work improves on this by attempting to arrive at a near real-time monitoring tool in aiding the EMS staff. Using data collected from 16 pigs during VF, the proposed wavelet methodology achieved an overall accuracy of 94% in successfully predicting the shock outcomes.
影响因子：
6.5
作者：
Povoas, HP;Weil, MH;Barbatsis, A
通讯作者：
Barbatsis, A