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| A Synthetic Algorithm of FECG Extraction from Single-Lead Abdominal Signals |
| Tian Fuying#* |
| School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China |
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Abstract In this paper, a synthetic algorithm was proposed to extract the fetal electrocardiogram (FECG) from single-lead abdominal signals. We extracted maternal electrocardiogram (MECG) and FECG successively and then calculated maternal and fetal heart rate. In the algorithm, we first applied Teager energy operator with parameter k (k=19) to protrude QRS waves of MECG, so that the location of maternal R peaks was detected correctly by simple threshold. Then we resampled between every adjacent R peaks to get same R-R interval T. After applying a comb filter whose teeth coincide with the maternal R-R interval T, we obtained the MECG with same R-R interval. And the real MECG was obtained by resampling between every adjacent R peaks in the filtered signals again to recover the original R-R intervals. The extracted MECG was subtracted from the abdominal signals. In the residual signal the QRS waves of FECG had better signal-noise-ratio. Next, the same procedure was applied on the residual signal to extract the FECG signal. We analyzed 8 sets of abdominal signals (total 26 channels) that were selected from the Physionet non-invasive FECG database. The sensitivity (Se), positive predictive value (PPV) and accuracy (F1) of fetal QRS waves detection were calculated. Results showed that the detection accuracy of fetal QRS waves reached 87.1%, with six channel even reached 100%. The maternal heart rate (MHR) and fetal heart rate (FHR) of each channel were also calculated. We found out that the MHRs, as well as the FHRs, showed good consistence with channels of the same set. In the same set, the maximum error of the mean MHR was 0.1 times per minute and the maximum error of mean FHR was 0.9 times per minute. Such a phenomenon also proved the reliability of the proposed algorithm.
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Received: 30 June 2016
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