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基于非负矩阵分解的胎儿心音图信号去噪

Foetal phonocardiographic signal denoising based on non-negative matrix factorization.

作者信息

Chourasia V S, Tiwari A K, Gangopadhyay R, Akant K A

机构信息

The LNM Institute of Information Technology, Post Sumel, Jamdoli, Jaipur (Rajasthan), India.

出版信息

J Med Eng Technol. 2012 Jan;36(1):57-66. doi: 10.3109/03091902.2011.638964. Epub 2011 Dec 3.

Abstract

Foetal phonocardiography (fPCG) is a non-invasive, cost-effective and simple technique for antenatal care. The fPCG signals contain vital information of diagnostic importance regarding the foetal health. However, the fPCG signal is usually contaminated by various noises and thus requires robust signal processing to denoise the signal. The main aim of this paper is to develop a methodology for removal of unwanted noise from the fPCG signal. The proposed methodology utilizes the non-negative matrix factorization (NMF) algorithm. The developed methodology is tested on both simulated and real-time fPCG signals. The performance of the developed methodology has been evaluated in terms of the gain in signal-to-noise ratio (SNR) achieved through the process of denoising. In particular, using the NMF algorithm, a substantial improvement in SNR of the fPCG signals in the range of 12-30 dB has been achieved, providing a high quality assessment of foetal well-being.

摘要

胎儿心音描记术(fPCG)是一种用于产前护理的非侵入性、经济高效且简单的技术。fPCG信号包含有关胎儿健康的具有诊断重要性的关键信息。然而,fPCG信号通常会受到各种噪声的污染,因此需要强大的信号处理来对信号进行降噪。本文的主要目的是开发一种从fPCG信号中去除不需要噪声的方法。所提出的方法利用非负矩阵分解(NMF)算法。所开发的方法在模拟和实时fPCG信号上进行了测试。已根据通过去噪过程实现的信噪比(SNR)增益来评估所开发方法的性能。特别是,使用NMF算法,fPCG信号的SNR在12 - 30 dB范围内有了显著提高,为胎儿健康状况提供了高质量评估。

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