Costanzo Di Maria
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
Authors
Chengyu Liu
Dingchang Zheng
Alan Murray
Philip Langley
Abstract
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.
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. https://doi.org/10.1088/0967-3334/35/8/1649
Acceptance Date | Jun 30, 2014 |
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Online Publication Date | Jul 29, 2014 |
Publication Date | Aug 1, 2014 |
Deposit Date | Mar 18, 2016 |
Publicly Available Date | Mar 18, 2016 |
Journal | Physiological management |
Print ISSN | 0967-3334 |
Publisher | IOP Publishing |
Peer Reviewed | Peer Reviewed |
Volume | 35 |
Issue | 8 |
Pages | 1649-1664 |
DOI | https://doi.org/10.1088/0967-3334/35/8/1649 |
Keywords | Non-invasive fetal ECG; Abdominal fetal ECG; ECG cancellation; Principal components analysis; Wavelet de-noising |
Public URL | https://hull-repository.worktribe.com/output/433758 |
Publisher URL | http://iopscience.iop.org/article/10.1088/0967-3334/35/8/1649/meta;jsessionid=96809BA805EA629D04C7A13B0CFA0A13.c2.iopscience.cld.iop.org |
Additional Information | This is the accepted version of an article published in Physiological measurement, 2014, v.35 issue 8. |
Contract Date | Mar 18, 2016 |
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Copyright Statement
© 2016 IOP Publishing
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