A novel approach to fetal ECG extraction and enhancement using blind source separation (BSS-ICA) and adaptive fetal ECG enhancer (AFE)

Gupta, Abhinav; Srivastava, Madhur; Khandelwal, Vineet

doi:10.1109/icics.2007.4449716

Cited by 13 publications

(7 citation statements)

References 10 publications

(11 reference statements)

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“…Most of the currently available hybrid methods utilize the ICA algorithm. Very interesting hybrid methods are for example combination of ICA, ensemble empirical mode decomposition (EEMD) and wavelet shrinkage (WS) [98], combination of ICA and adaptive fECG enhancer (AFE) [99], combination of ICA and projective filtering (PF) [100], combination of ICA and PCA [101], combination of singular value decomposition (SVD) and ICA [102], etc. In our future research, we aim to test some of the most promising methods and modify our system according to the results.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Novel Hybrid Extraction Systems for Fetal Heart Rate Variability Monitoring Based on Non-Invasive Fetal Electrocardiogram

et al. 2019

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This study focuses on the design, implementation and subsequent verification of a new type of hybrid extraction system for noninvasive fetal electrocardiogram (NI-fECG) processing. The system designed combines the advantages of individual adaptive and non-adaptive algorithms. The pilot study reviews two innovative hybrid systems called ICA-ANFIS-WT and ICA-RLS-WT. This is a combination of independent component analysis (ICA), adaptive neuro-fuzzy inference system (ANFIS) algorithm or recursive least squares (RLS) algorithm and wavelet transform (WT) algorithm. The study was conducted on clinical practice data (extended ADFECGDB database and Physionet Challenge 2013 database) from the perspective of non-invasive fetal heart rate variability monitoring based on the determination of the overall probability of correct detection (ACC), sensitivity (SE), positive predictive value (PPV) and harmonic mean between SE and PPV (F1). System functionality was verified against a relevant reference obtained by an invasive way using a scalp electrode (ADFECGDB database), or relevant reference obtained by annotations (Physionet Challenge 2013 database). The study showed that ICA-RLS-WT hybrid system achieve better results than ICA-ANFIS-WT. During experiment on ADFECGDB database, the ICA-RLS-WT hybrid system reached ACC > 80 % on 9 recordings out of 12 and the ICA-ANFIS-WT hybrid system reached ACC > 80 % only on 6 recordings out of 12. During experiment on Physionet Challenge 2013 database the ICA-RLS-WT hybrid system reached ACC > 80 % on 13 recordings out of 25 and the ICA-ANFIS-WT hybrid system reached ACC > 80 % only on 7 recordings out of 25. Both hybrid systems achieve provably better results than the individual algorithms tested in previous studies. INDEX TERMS Noninvasive fetal electrocardiography, independent component analysis (ICA), adaptive neuro fuzzy inference system (ANFIS), recursive least squares (RLS), wavelet transform (WT), ICA-ANFIS-WT, ICA-RLS-WT, hybrid methods, fetal heart rate variability monitoring, extraction systems.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Novel Hybrid Extraction Systems for Fetal Heart Rate Variability Monitoring Based on Non-Invasive Fetal Electrocardiogram

et al. 2019

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“…For the reasons listed above, the major challenge nowadays is to enable morphological analysis from the non-invasively recorded signal. Some of the studies proved that it is possible, mainly using advanced hybrid non-adaptive methods [ 102 , 104 , 105 , 110 ]. It should be noted that specific technical aspects are associated with the morphological analysis, mainly the sampling frequency that should be higher than 500 Hz that is generally used for the fHR monitoring.…”

Section: Discussionmentioning

confidence: 99%

“…Based on the extensive overview presented herein, we conclude that hybrid methods, such as ICA-EEMD-WS [ 102 ], ICA & AF [ 104 ], ICA & PF [ 105 ], and BA & ZA [ 110 ], seem to be the most promising non-adaptive methods for NI-fECG signal processing. The authors believe that the application of selected NI-fECG methods will lead to the development of a completely new diagnostic method using non-invasively recorded fHR data (fHR based on detection of NI-fECG R-R interval) to determine the fetal hypoxic state in combination with non-invasively obtained T/QRS ratio, i.e., enable non-invasive fECG ST segment analysis.…”

Section: Discussionmentioning

confidence: 99%

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Non-Adaptive Methods for Fetal ECG Signal Processing: A Review and Appraisal

Jaroš

Martínek

Kahánková

2018

Sensors

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Fetal electrocardiography is among the most promising methods of modern electronic fetal monitoring. However, before they can be fully deployed in the clinical practice as a gold standard, the challenges associated with the signal quality must be solved. During the last two decades, a great amount of articles dealing with improving the quality of the fetal electrocardiogram signal acquired from the abdominal recordings have been introduced. This article aims to present an extensive literature survey of different non-adaptive signal processing methods applied for fetal electrocardiogram extraction and enhancement. It is limiting that a different non-adaptive method works well for each type of signal, but independent component analysis, principal component analysis and wavelet transforms are the most commonly published methods of signal processing and have good accuracy and speed of algorithms.

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“…The LMS filter in combination with WT was used to extract the fECG efficiently in [59], [85]. The combination of LMS and ICA also achieved promising results in [70]. Other extended variants of this filter normalized LMS (NLMS), delayed LMS (DLMS) and block LMS (BLMS) were compared in [86], where the best results were achieved using the BLMS algorithm.…”

Section: B Methods For Fecg Signal Extractionmentioning

confidence: 99%

Non-Invasive Fetal Electrocardiogram Extraction Based on Novel Hybrid Method for Intrapartum ST Segment Analysis

et al. 2021

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This study focuses on non-invasive fetal electrocardiogram extraction based on a novel hybrid method, which combines the advantages of non-adaptive and adaptive approaches for non-invasive fetal electrocardiogram morphological analysis. Besides estimating fetal heart rate, which is the main parameter used in the clinical practice, this study provides non-invasive ST segment analysis on data from Abdominal and Direct Fetal Electrocardiogram Database consisting of simultaneous traditionalgold standard invasive fetal scalp electrode and non-invasive fetal electrocardiogram recorded during delivery. This innovative approach utilizing the combination of independent component analysis and recursive least squares algorithms has the potential to extract valuable information from non-invasive fetal electrocardiogram in order to identify eventual sign of fetal distress. This was a prospective observational study of non-invasive fetal electrocardiogram, using 4 abdominally sited electrodes, against the traditional fetal scalp electrode on 8 patients. In terms of fetal heart rate estimation, the accuracy was high for all 8 tested patients with average value equaled 0.20 beats per minute and average value of 1.96 standard deviation equaled 5.80 beats per minute. In 7 patients, it was possible to perform the ST segment analysis with high accuracy in determining T/QRS in comparison with the reference fetal scalp electrode signal with average values and 1.96 standard deviation equaled 0.008 and 0.031 respectively. This study thus demonstrates that ST segment analysis is feasible using non-invasive fECG using the proposed hybrid method. INDEX TERMS Non-invasive fetal electrocardiography (NI-fECG), fetal heart rate (fHR), ST segment analysis (ST-analysis), hybrid method (HM), independent component analysis and recursive least squares (ICA-RLS), electronic fetal monitoring (EFM), fetal distress (FD), fetal scalp electrode (FSE).

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A novel approach to fetal ECG extraction and enhancement using blind source separation (BSS-ICA) and adaptive fetal ECG enhancer (AFE)

Cited by 13 publications

References 10 publications

Novel Hybrid Extraction Systems for Fetal Heart Rate Variability Monitoring Based on Non-Invasive Fetal Electrocardiogram

Novel Hybrid Extraction Systems for Fetal Heart Rate Variability Monitoring Based on Non-Invasive Fetal Electrocardiogram

Non-Adaptive Methods for Fetal ECG Signal Processing: A Review and Appraisal

Non-Invasive Fetal Electrocardiogram Extraction Based on Novel Hybrid Method for Intrapartum ST Segment Analysis

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