A Comparison of Five Algorithms for Fetal Magnetocardiography Signal Extraction

Diana Escalona-Vargas, Hau tieng Wu, Martin G. Frasch, Hari Eswaran

Research output: Contribution to journalArticlepeer-review


Fetal magnetocardiography (fMCG) provides accurate and reliable measurements of electrophysiological events in the fetal heart and is capable of studying fetuses with congenital heart diseases. A variety of techniques exist to extract the fMCG signal with the demand for non-invasively obtained fetal cardiac information. To the best of our knowledge, there is no comparative study published in the field as to how the various extraction algorithms perform. We perform a comparative study of the ability of five methods to extract the fMCG using real biomagnetic signals, two of those methods are applied to real fMCG data for the first time. Biomagnetic signals were recorded and processed with each of the five methods to obtain fMCG. The R peaks of the fMCG traces were obtained via a peak-detection algorithm. From whole recording for each method, the fetal heart rate (FHR) was calculated and used to perform FHR variability (FHRV) analysis. Additionally, we calculated durations from the PQRST complex from time-averaged data during sinus rhythm. The five methods recovered the fMCG signals, but two of them were able to extract cleaner fMCG and the morphology was observed from the continuous data. The time-averaged data showed very similar morphologies between methods, but two of them displayed a signal amplitude reduction on the R-waves and T-waves. Values of PQRST durations, FHR and FHRV were in the range of previous fetal cardiac studies. We have compared five methods for fMCG extraction and showed their ability to perform fMCG analysis.

Original languageEnglish (US)
Pages (from-to)483-487
Number of pages5
JournalCardiovascular Engineering and Technology
Issue number3
StatePublished - Sep 15 2018


  • Cardiac time intervals
  • Fetal magnetocardiography
  • Signal processing
  • Variability analysis

ASJC Scopus subject areas

  • Biomedical Engineering
  • Cardiology and Cardiovascular Medicine


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