用于心血管疾病监测的可穿戴式心电描记仪

Y. Rong, Matthew Fynn, S. Nordholm, Serena Siaw, G. Dwivedi
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引用次数: 1

摘要

在本文中,我们介绍了一种新的可穿戴多通道心音图(PCG)和心电图(ECG)设备,用于心血管疾病(CVD)预筛查和监测,这是由科廷大学的研究人员与一家健康技术初创公司滴答心脏(滴答心脏)合作开发的。为了提高心音信号的完整性,提出了一种基于迭代维纳滤波的噪声消除算法。实验结果表明,与现有方法相比,该算法在抑制200 ~ 300 Hz噪声方面具有更好的性能。提出了一种基于卷积神经网络的分类器,该分类器同时利用心电和心电信号来提高心血管疾病的预筛查精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wearable Electro-Phonocardiography Device for Cardiovascular Disease Monitoring
In this paper, we present a new wearable multichannel phonocardiography (PCG) and electrocardiography (ECG) device for cardiovascular disease (CVD) pre-screening and monitoring developed recently by researchers at Curtin University in collaboration with Ticking Heart, a health-tech start-up. An iterative Wiener filter based noise cancelation algorithm is proposed to improve the integrity of heart sound signals. We show that compared with an existing approach, the proposed algorithm has a better performance in suppressing the noise at 200-300 Hz. A convolutional neural network based classifier is implemented which exploits both the ECG and PCG signals to improve the pre-screening accuracy of CVD.
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