Document Detail


Detection of fetal electrocardiogram signals using matched filters with adaptive normalisation.
MedLine Citation:
PMID:  9246855     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The authors discuss the application of matched litters to the detection of R-waves in fetal electrocardiogram (FECG) data, recorded during labour using a scalp electrode. When using the basic matched filter, one correlates a template representing the clean signal with the noisy signal. This method is optimal when the underlying noise is white in nature. However, it is known that false detection of R-waves can occur in the presence of extraneous peaks which have a similar shape to the fetal R-wave. It is proposed to switch between two different normalisations of the impulse response of the matched filter to alleviate this problem. When the signal-to-noise ratio is lower than a predetermined threshold, then normalisation to the geometric mean of the template and noisy data energies is carried out, otherwise only normalisation to the template energy is made. In the former case, the background noise and spikes that are larger than the underlying FECG are attenuated, hence increasing the probability of detection of the R-waves. In the latter case, noise, which has a lower amplitude than the underlying R-wave, is reduced. The effectiveness of this method is demonstrated by application to scalp electrode data.
Authors:
N M Gibson; M S Woolfson; J A Crowe
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Medical & biological engineering & computing     Volume:  35     ISSN:  0140-0118     ISO Abbreviation:  Med Biol Eng Comput     Publication Date:  1997 May 
Date Detail:
Created Date:  1997-08-22     Completed Date:  1997-08-22     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  7704869     Medline TA:  Med Biol Eng Comput     Country:  ENGLAND    
Other Details:
Languages:  eng     Pagination:  216-22     Citation Subset:  IM    
Affiliation:
Department of Electrical and Electronic Engineering, University of Nottingham, UK.
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MeSH Terms
Descriptor/Qualifier:
Electrocardiography / instrumentation*
Fetal Monitoring / instrumentation*
Humans
Signal Processing, Computer-Assisted*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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