Extraction of temporally correlated sources with its application to non-invasive fetal electrocardiogram extraction

Extraction of foetal ECG from abdominal ECG by nonlinear transformation and estimations

BACKGROUND AND OBJECTIVE

This paper proposes a simple yet effective method for the extraction of foetal ECG from abdominal ECG which is necessary due to similar spatial and temporal content of mother and foetal ECG.

METHODS

The proposed algorithm for extraction of foetal ECG (fECG) from abdominal signal uses single channel. Pre-processing of abdominal ECG (abdECG) has been done to eliminate noise and condition the signal. The maternal ECG R-peaks have been detected based on thresholding, first order Gaussian differentiation and zero cross detection on pre-processed signal. Having identified R-peaks and pre-processed signal as base, using Maximum Likelihood Estimation, one beat including QRS complex morphology of maternal ECG (mECG) has been constructed. Extraction of maternal ECG from abdECG is done based on the constructed beat, R-peak locations and its corresponding QRS complex of abdECG. Extracted mECG has been cancelled from abdECG. This results in foetal ECG with residual noise. The noise has been reduced by Polynomial Approximation and Total Variation (PATV) to improve SNR. This approach ensures no loss of partially or completely overlapped fECG signals due to mECG removal. The algorithm is tested on three database namely daISy (DB_I), Physiobank challenge 2013 (DB_II) and abdominal and direct foetal ECG database (adfecgdb) of Physiobank (DB_III).

RESULTS

The algorithm detected no false positives or false negatives with certain channel for DB_I, DB_II and DB_III which shows that the proposed algorithm can achieve good performance. Overall accuracy and sensitivity of the system is 98.53% and 100% for DB_I. Best accuracy and sensitivity of 97.77% and 98.63% are obtained for DB_II. Best accuracy of 92.41% and sensitivity of 93.8% are obtained for DB_III. Correlation coefficient between actual foetal heart rate (fHR) and estimated fHR of 0.66 for DB_II and 0.59 for DB_III is obtained. The method has obtained overall F1 score of 99.25% for DB_I, 96.04% for DB_II and 94.25% for DB_III. It has obtained a best MSE of fHR and overall MSE of R-R interval which is 10.8bpm² and 2.2 ms for DB_II, 12bpm² and 2.14 ms for DB_III.

CONCLUSION

The results for different public databases show that the proposed method is capable of providing good results. The foetal QRS, R-peaks and R-R intervals have also been obtained in this method. Thus, it gives a significant contribution in the required area of research.

Robust fetal QRS detection from noninvasive abdominal electrocardiogram based on channel selection and simultaneous multichannel processing

The purpose of this study is to provide a new method for detecting fetal QRS complexes from non-invasive fetal electrocardiogram (fECG) signal. Despite most of the current fECG processing methods which are based on separation of fECG from maternal ECG (mECG), in this study, fetal heart rate (FHR) can be extracted with high accuracy without separation of fECG from mECG. Furthermore, in this new approach thoracic channels are not necessary. These two aspects have reduced the required computational operations. Consequently, the proposed approach can be efficiently applied to different real-time healthcare and medical devices. In this work, a new method is presented for selecting the best channel which carries strongest fECG. Each channel is scored based on two criteria of noise distribution and good fetal heartbeat visibility. Another important aspect of this study is the simultaneous and combinatorial use of available fECG channels via the priority given by their scores. A combination of geometric features and wavelet-based techniques was adopted to extract FHR. Based on fetal geometric features, fECG signals were divided into three categories, and different strategies were employed to analyze each category. The method was validated using three datasets including Noninvasive fetal ECG database, DaISy and PhysioNet/Computing in Cardiology Challenge 2013. Finally, the obtained results were compared with other studies. The adopted strategies such as multi-resolution analysis, not separating fECG and mECG, intelligent channels scoring and using them simultaneously are the factors that caused the promising performance of the method.

Applicability of adaptive noise cancellation to fetal heart rate detection using photoplethysmography

In this paper, an approach based on adaptive noise cancellation (ANC) is evaluated for extraction of the fetal heart rate using photoplethysmographic signals from the maternal abdomen. A simple optical model is proposed in which the maternal and fetal blood pulsations result in emulated signals where the lower SNR limit (fetal to maternal) is -25dB. It is shown that a recursive least-squares algorithm is capable of extracting the peaks of the fetal PPG from these signals, for typical values of maternal and fetal tissues.