A new method for the extraction of fetal ECG from the dependent abdominal signals using blind source separation and adaptive noise cancellation techniques

详细信息    查看全文

• 作者：Abdelghani Ghazdali ; Abdelilah Hakim…
• 关键词：Blind source separation ; Fetal electrocardiogram extraction ; Copula ; Bilateral TV filter ; Dependent sources
• 刊名：Theoretical Biology and Medical Modelling
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：12
• 期：1
• 全文大小：3,290 KB
• 刊物主题：Biomedicine general; Systems Biology; Physiological, Cellular and Medical Topics; Statistics for Life Sciences, Medicine, Health Sciences;
• 出版者：BioMed Central
• ISSN：1742-4682

文摘

Background The electrocardiogram (ECG) is a diagnostic tool that records the electrical activity of the heart, and depicts it as a series of graph-like tracings, or waves. Being able to interpret these details allows diagnosis of a wide range of heart problems. Fetal electrocardiogram (FECG) extraction has an important impact in medical diagnostics during the mother pregnancy period. Since the observed FECG signals are often mixed with the maternal ECG (MECG) and the noise induced by the movement of electrodes or by mother motion, the separation process of the ECG signal sources from the observed data becomes quite complicated. One of its complexity is when the ECG sources are dependent, thus, in this paper we introduce a new approach of blind source separation (BSS) in the noisy context for both independent and dependent ECG signal source. This approach consist in denoising the observed ECG signals using a bilateral total variation (BTV) filter; then minimizing the Kullbak-Leibler divergence between copula densities to separate the FECG signal from the MECG one.