A New Method for Biomedical Signal Processing with EMD and ICA Approach

Abstract:

Faint signal extraction is always a difficult issue in biomedical signal processing field, because the desired signal is often submerged in several relatively large signals or noises. A novel faint signal processing method based on Empirical Mode Decomposition (EMD) and Independent Component Analysis (ICA) is developed to enhance the sensitivity and reliability of faint signal detection. This novel method includes two major steps, which is, firstly the decomposition of the biomedical composite signal using EMD, then the classification or extraction of the desired faint signal component through ICA. This paper explored the working principles and the performance of this novel signal processing method under the specific biomedical environment of fetal electrocardiogram extraction (FECG). The experimental results show that the proposed method has better extraction effect and quality compared with traditional ICA methods.

• Periodical: Advanced Materials Research (Volumes 546-547)
• Pages: 548-552
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.546-547.548
• Online since: July 2012
• Authors: Wei Yu, Qiang Han, Jing Jing Ma, Pei Xie
• Keywords: Empirical Mode Decomposition (EMD), Fetal Electrocardiogram (FECG), Independent Component Analysis (ICA)

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