利用盲源分离技术提取母体心电图中的胎儿心跳

Proceedings of the 2019 11th International Conference on Bioinformatics and Biomedical Technology Pub Date : 2019-05-29 DOI:10.1145/3340074.3340087

Maliha Atteeq, Muhammad Fahad Khan, Adnan N. Qureshi

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引用次数: 2

摘要

通过心音图进行胎儿监护是非侵入性的，也是非常具有挑战性的技术。了解胎儿的心脏状况是非常重要的。从母心音中提取胎儿心跳是一项非常具有挑战性和困难的任务，因为存在其他声音，如母器官声、母呼吸声和外部噪音。基准数据集和文献也不可用。本研究采用STFT等盲源分离技术从母体心跳中提取胎儿心跳。设拉子大学胎儿心音数据库Physionet已被使用。92个母亲的心音被使用。可以看出，该算法很好地将混合源分离为母心音和胎儿心音。

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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Fetus Heart Beat Extraction from Mother's PCG Using Blind Source Separation

Fetal monitoring through phonocardiography is non-invasive and very challenging technique. It is very crucial to know about the fetus heart status. Extraction of fetus heart beat from mother heart sound is very challenging and difficult task due to the presence of additional sounds like mother organ sound, mother respiration and external noises. Benchmarked datasets and literature are also not available. In this research we extract fetus heart beat from mother beat using Blind source separation technique like STFT. Shiraz University Fetal Heart Sounds Database of Physionet has been used. 92 maternal heart sounds are used. It can be seen that the algorithm well separates the mixed source into maternal and fetal heart sounds.

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Proceedings of the 2019 11th International Conference on Bioinformatics and Biomedical Technology

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