Data di Pubblicazione:
2013
Abstract:
Non-invasive monitoring of fetal cardiac activity is of great clinical interest to assess fetal health. To date, however, difficulties in detecting fetal beats from abdominal mother recordings prevented the possibility of obtaining reliable results. In this study a multi-step approach for the analysis of non-invasive fetal ECG is proposed. The first steps concern the pre-processing stages of baseline removal and power line interference canceling. The successive operations are: Independent Component Analysis (ICA) for maternal ECG extraction; mother QRS detection; maternal ECG canceling using a PQRST approximation obtained by weighted Singular Value Decomposition (SVD); second ICA applied to enhance the fetal ECG signal; fetal QRS detection. The results obtained in Physionet Challenge 2013 on the test sets are expressed as two scores (HRmse and RRrmse) measuring respectively the matching between the reference annotations of fetal HR and RR time series and those estimated with the developed software. The results obtained on the learning set are: sensitivity=99.4%, positive predictive accuracy=99.2% and HRmse=1.52 bpm2, RRrmse=2.11 ms. The scores for the open test set are: HRmse=34.0 bpm2, RRrmse=5.10 ms. The scores for the hidden test (open source section) are: HRmse=187 bpm2, RRrmse=21.0 ms.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
fetal electrocardiography; fetal QRS detection; signal processing
Elenco autori:
Billeci, Lucia; Tartarisco, Gennaro; Balocchi, Rita; Pioggia, Giovanni; Varanini, Maurizio
Link alla scheda completa:
Titolo del libro:
Computing in Cardiology Conference (CinC), 2013
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