Abnormal Heart Sound Detection by Using Temporal Convolutional Network

Keqi Liu, Lei Yuan, Cheng-Tao Huang, Wenyuan Wu, Qiangwei Wang, Gang Wu
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引用次数: 2

Abstract

Abnormal heart sound detection is great of significance because of the frequent occurrence of heart diseases. However, the automatic diagnosis for abnormal heart sound has a high requirement for domain knowledge and the signal noise poses an increased difficulty of diagnosis. In this paper, we propose a temporal convolutional network (TCN) to automatically detect abnormal heart sounds. Specifically, a noise removing technology is applied to original signals. Then, a TCN architecture is carefully designed to adapt the properties of heartbeat sound. The proposed method is tested on the Physionet dataset, and the results show our method contains potential ability in abnormal heart sound detection.
基于时间卷积网络的异常心音检测
由于心脏疾病的多发,异常心音检测具有重要意义。然而,异常心音的自动诊断对领域知识要求较高,且信号噪声增加了诊断难度。在本文中,我们提出了一种时间卷积网络(TCN)来自动检测异常心音。具体来说,对原始信号采用了去噪技术。然后,仔细设计了TCN架构,以适应心跳声的特性。在Physionet数据集上进行了测试,结果表明该方法在异常心音检测中具有潜在的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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