文章基本信息

标题：Least Mean Squares Adaptive Algorithms Optimization for Fetal Phonocardiogram Extraction
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作者：Radana Kahankova ; Radek Martinek ; Rene Jaros 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：6
页码：60-65
DOI：10.1016/j.ifacol.2018.07.130
语种：English
出版社：Elsevier
摘要：AbstractThe paper deals with extraction of fetal phonocardiogram (fPCG) from the abdominal signal mixture by using adaptive filters based on Least Mean Squares (LMS) algorithms. Optimal setting of the filter parameters is a vital condition to ensure efficiency of adaptive filters. In this paper, we suggest ideal parameters setting for this purpose. The filtration quality was assessed by means of objective parameters, namely Signal to Noise Ratio (SNR) and Positive Predictive Value (PPV). The results showed that if optimized, LMS-based adaptive algorithms are efficient in suppressing maternal component in the composed abdominal signal.
关键词：KeywordsFetal Phonocardiogram (fPCG)OptimizationAdaptive algorithmsExtractionLeast Mean Squares (LMS)Delayed Least Mean Squares (DLMS)Signal to Noise Ratio (SNR)Positive Predictive Value (PPV)