Adaptive signal processing techniques for extracting fetal electrocardiograms from noninvasive measurements

@article{Jenkins2014AdaptiveSP,
  title={Adaptive signal processing techniques for extracting fetal electrocardiograms from noninvasive measurements},
  author={William K. Jenkins and Han Ding and Matthew Zenaldin and A. De Salvia and R. M. Collins},
  journal={2014 IEEE 57th International Midwest Symposium on Circuits and Systems (MWSCAS)},
  year={2014},
  pages={639-642}
}
  • W. Jenkins, H. Ding, R. M. Collins
  • Published 25 September 2014
  • Medicine
  • 2014 IEEE 57th International Midwest Symposium on Circuits and Systems (MWSCAS)
In clinical medicine fetal electrocardiograms (ECGs) are useful for monitoring fetal health during pregnancy. This research investigates a variety of adaptive filtering techniques to remove maternal interference from fetal ECGs and to determine which techniques are most effective under varying circumstances. Experimental results suggest that a sequential combination of adaptive linear prediction coding (LPC), adaptive noise cancellation (ANC), and IIR comb filtering provides an effective… 

Figures from this paper

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Experimental results demonstrate how various combinations of time-domain and transform-domain adaptive filters can effectively extract the fetal component from noninvasive abdominal fetal ECG's and illustrate that sequential processing followed by single stage comb filtering and newly proposed adaptive comb filtering is an effective form of sequential processing.

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Experimental results illustrate that sequential LPC-ANC processing followed by the newly proposed adaptive comb filtering is an effective form of sequential processing.

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