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Extracting fetal heart beats from maternal abdominal recordings: Selection of the optimal principal components

Di Maria, Costanzo; Liu, Chengyu; Zheng, Dingchang; Murray, Alan; Langley, Philip


Costanzo Di Maria

Chengyu Liu

Dingchang Zheng

Alan Murray


This study presents a systematic comparison of different approaches to the automated selection of the principal components (PC) which optimise the detection of maternal and fetal heart beats from non-invasive maternal abdominal recordings. A public database of 75 4-channel non-invasive maternal abdominal recordings was used for training the algorithm. Four methods were developed and assessed to determine the optimal PC: (1) power spectral distribution, (2) root mean square, (3) sample entropy, and (4) QRS template. The sensitivity of the performance of the algorithm to large-amplitude noise removal (by wavelet de-noising) and maternal beat cancellation methods were also assessed. The accuracy of maternal and fetal beat detection was assessed against reference annotations and quantified using the detection accuracy score F1 [2*PPV*Se / (PPV + Se)], sensitivity (Se), and positive predictive value (PPV). The best performing implementation was assessed on a test dataset of 100 recordings and the agreement between the computed and the reference fetal heart rate (fHR) and fetal RR (fRR) time series quantified. The best performance for detecting maternal beats (F1 99.3%, Se 99.0%, PPV 99.7%) was obtained when using the QRS template method to select the optimal maternal PC and applying wavelet de-noising. The best performance for detecting fetal beats (F1 89.8%, Se 89.3%, PPV 90.5%) was obtained when the optimal fetal PC was selected using the sample entropy method and utilising a fixed-length time window for the cancellation of the maternal beats. The performance on the test dataset was 142.7 beats2/min2 for fHR and 19.9 ms for fRR, ranking respectively 14 and 17 (out of 29) when compared to the other algorithms presented at the Physionet Challenge 2013.

Publication Date Aug 1, 2014
Journal Physiological management
Print ISSN 0967-3334
Electronic ISSN 1361-6579
Publisher IOP Publishing
Peer Reviewed Peer Reviewed
Volume 35
Issue 8
Pages 1649-1664
APA6 Citation Di Maria, C., Liu, C., Zheng, D., Murray, A., & Langley, P. (2014). Extracting fetal heart beats from maternal abdominal recordings: Selection of the optimal principal components. Physiological Measurement, 35(8), 1649-1664.
Keywords Non-invasive fetal ECG; Abdominal fetal ECG; ECG cancellation; Principal components analysis; Wavelet de-noising
Publisher URL;
Additional Information This is the accepted version of an article published in Physiological measurement, 2014, v.35 issue 8.


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