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Arrhythmia Detection Using MIT-BIH Dataset: A Review

机译:使用MIT-BIH数据集进行心律失常检测:审查

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摘要

Arrhythmia is a medical condition when the normal pumping mechanism of the human heart becomes irregular. The detection of arrhythmia is one of the most important step for diagnose the condition that can play an important role in aiding cardiologist with decision. In this paper a survey is carried out over various methods such as SVM, Neural networks, Wavelet transforms, etc focused to perform arrhythmia detection especially using MIT-BIH database. There are number of challenges in detection of arrhythmias in heart beat dataset. Although many researchers have suggested various approaches to resolve them, still there are requirements for invention and improvements.
机译:当人心脏的正常泵送机制变得不规则时,心律失常是一种医学条件。心律失常的检测是诊断可能在辅助心脏病专家决定中发挥重要作用的最重要步骤之一。在本文中,通过各种方法进行了一项调查,例如SVM,神经网络,小波变换等,重点是尤其使用MIT-BIH数据库进行心律失常检测。在心跳数据集中检测心律失常存在挑战数量。虽然许多研究人员建议解决它们的各种方法,但仍有对发明的要求和改进。

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