Fetal heart rate extraction from composite maternal ECG using complex continuous wavelet transform

Karvounis, Evaggelos; Papaloukas, Costas; Fotiadis, D.I.; Michalis, Lampros K.

doi:10.1109/cic.2004.1443044

Cited by 49 publications

(35 citation statements)

References 8 publications

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“…A major disadvantage of the BSS based techniques is that they require a large number of recorded observed mixtures (ECG leads) in order to obtain satisfactory results. Besides BSS approaches, various research efforts have been proposed in the literature, including matched filtering [5], adaptive neuro-fuzzy inference systems [6], dynamic neural networks [7], temporal structure [8], fuzzy logic [9], frequency tracking [10], polynomial networks [11], wavelets [12], real-time signal processing [13] and time-frequency analysis [14]. Most of the approaches proposed in the literature, are evaluated using simulated signals or/and a very small dataset of real recordings.…”

Section: Introductionmentioning

confidence: 99%

Maternal and fetal heart rate extraction from abdominal recordings using multi-scale principal components analysis

Karvounis

Fotiadis

2007

2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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A three-stage methodology for the extraction of maternal and fetal heart rate using abdominal ECG leads, is presented. In the first stage, the maternal R-peaks and fiducial points (maternal QRS onset and offset) are detected, using multiscale principal components analysis (MSPCA) and the Smoothed Nonlinear Energy Operator (SNEO). Maternal fiducial points are used to eliminate the maternal QRS complexes from the abdominal ECG recordings. In the second stage, again MSPCA and SNEO are employed in order to detect the fetal heart beats that do not overlap with the maternal QRSs (eliminated from the first stage). The extraction of the fetal heart rate is accomplished in the last stage, using a histogram based technique in order to identify the positions of the fetal heart beats that overlap with the maternal QRSs. Real signals, recorded from different pregnant women and different weeks of gestation, are used for the evaluation of the proposed methodology and the obtained results indicate high performance (accuracy 95%).

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Section: Introductionmentioning

confidence: 99%

Maternal and fetal heart rate extraction from abdominal recordings using multi-scale principal components analysis

Karvounis

Fotiadis

2007

2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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“…The wavelet transform (WT) is another approach that has been proposed for FECGs processing. Several techniques for noise removal and detection of fetal waveforms have been used, involving Gabor-8 wavelets and Lipschitz exponent's theory [16], bi-orthogonal quadratic spline wavelet, modulus maxima theory [17] and complex continuous wavelets [18].…”

Section: Introductionmentioning

confidence: 99%

A Method for Fetal Heart Rate Extraction Based on Time-Frequency Analysis

Karvounis

Tsipouras

Fotiadis

et al. 2006

19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)

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A three-stage method for fetal heart rate extraction, from abdominal ECG recordings, is proposed. In the first stage the maternal R-peaks and fiducial points (QRS onset and offset) are detected, using time-frequency analysis, and the maternal QRS complexes are eliminated. The second stage locates the positions of the candidate fetal R-peaks, using complex wavelets and pattern matching theory techniques. In the third stage, the fetal R-peaks that overlap with the maternal QRS complexes are found. The method is validated using a dataset of 4 long duration recordings and the obtained results indicate high detection ability of the method (96% accuracy).

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“…In 2004, Karvounis et al [18] discovered that the complex continuous wavelet transform (CCWT) and modulus maxima theory can also be used to detect of the QRS complexes of the fetus cardiac activity using multi-channel maternal ECG recordings. For a non-stationary signal, CWT can be used to identify stationary sections of the data stream and to locate and characterize singularities.…”

Section: S(t)= R(t)[f(t) + M(t) + N(t)] the Terms F(t) M(t)mentioning

confidence: 99%

Techniques of FECG signal analysis: detection and processing for fetal monitoring

Hasan¹,

Ibrahimy²,

Reaz³

2007

WIT Transactions on Biomedicine and Health, Vol 12

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Fetal heart rate monitoring is a technique for obtaining important information about the condition of a fetus during pregnancy and labor, by detecting the FECG signal generated by the heart of the fetus. The ultimate reason for the interest in FECG signal analysis is in clinical diagnosis and biomedical applications. The extraction and detection of the FECG signal from composite abdominal signals with powerful and advance methodologies is becoming a very important requirement in fetal monitoring. The purpose of this review paper is to illustrate the various methodologies and algorithms on FECG signal detection and analysis to provide efficient and effective ways of understanding the FECG signal and its nature. A comparative study has been carried out to show the performance of various methods. This paper opens up a passage to biomedical researchers, physicians and end users to advocate an excellent understanding of FECG signal and its analysis procedures for fetal heart rate monitoring system by providing valuable information to help them in developing more dominant, flexible and resourceful applications.

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Fetal heart rate extraction from composite maternal ECG using complex continuous wavelet transform

Cited by 49 publications

References 8 publications

Maternal and fetal heart rate extraction from abdominal recordings using multi-scale principal components analysis

Maternal and fetal heart rate extraction from abdominal recordings using multi-scale principal components analysis

A Method for Fetal Heart Rate Extraction Based on Time-Frequency Analysis

Techniques of FECG signal analysis: detection and processing for fetal monitoring

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