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AFC-ECG: An Adaptive Fuzzy ECG Classifier

机译:AFC-ECG:自适应模糊ECG分类器

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摘要

After long-term exploration, it has been well established for the mechanisms of electrocardiogram (ECG) in health monitoring of cardiovascular system. Within the frame of an intelligent home healthcare system, our research group is devoted to researching/developing various mobile health monitoring systems, including the smart ECG interpreter. Hence, in this paper, we introduce an adaptive fuzzy ECG classifier with orientation to smart ECG interpreters. It can parameterize the incoming ECG signals and then classify them into four major types for health reference: Normal (N), Premature Atria Contraction (PAC), Right Bundle Block Beat (RBBB), and Left Bundle Block Beat (LBBB).
机译:经过长期的探索,对于心血管系统健康监测中的心电图(ECG)机制已经确立。在智能家庭保健系统的框架内,我们的研究小组致力于研究/开发各种移动健康监测系统,包括智能ECG解释器。因此,在本文中,我们介绍了一种针对智能ECG解释器的自适应模糊ECG分类器。它可以对传入的ECG信号进行参数化,然后将其分为四种主要类型以供健康参考:正常(N),过早心房收缩(PAC),右束支传导节律(RBBB)和左束支传导节律(LBBB)。

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