利用 ECG 与某些 EMD 函数的相关性进行心室颤动的区分。
Exploiting correlation of ECG with certain EMD functions for discrimination of ventricular fibrillation.
机构信息
Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh.
出版信息
Comput Biol Med. 2011 Feb;41(2):110-4. doi: 10.1016/j.compbiomed.2010.12.005. Epub 2011 Jan 14.
Ventricular fibrillation (VF) is a life-threatening cardiac arrhythmia. A high impulse current is required in this stage to save lives. In this paper, an empirical mode decomposition (EMD) based algorithm is presented to separate VF from other arrhythmias. The characteristics of the VF signal has high degree of similarity with the intrinsic mode functions (IMFs) of the EMD decomposition in comparison to other ECG pathologies. This high correlation between the VF signal and its certain IMFs is exploited to separate VF from other cardiac pathologies. Reliable databases are used to verify effectiveness of our algorithm and the results demonstrate superiority of our proposed technique compared to other well-known techniques of VF discrimination.
心室颤动（VF）是一种危及生命的心律失常。在这个阶段需要高脉冲电流来挽救生命。本文提出了一种基于经验模态分解（EMD）的算法，用于将 VF 与其他心律失常区分开来。与其他 ECG 病理相比，VF 信号的特征与 EMD 分解的固有模式函数（IMF）具有高度相似性。利用 VF 信号与其某些 IMF 之间的这种高度相关性将 VF 与其他心脏病理区分开来。可靠的数据库用于验证我们算法的有效性，结果表明，与其他著名的 VF 鉴别技术相比，我们提出的技术具有优越性。
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