2003
DOI: 10.1109/tbme.2002.807642
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Abstract: An algorithm based on digital filtering, adaptive thresholding, statistical properties in the time domain, and differencing of local maxima and minima has been developed for the simultaneous measurement of the fetal and maternal heart rates from the maternal abdominal electrocardiogram during pregnancy and labor for ambulatory monitoring. A microcontroller-based system has been used to implement the algorithm in real-time. A Doppler ultrasound fetal monitor was used for statistical comparison on five volunteer… Show more

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Cited by 81 publications
(31 citation statements)
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“…Therefore, the maternal contribution was not totally suppressed at the point in the FECG signal. [9] Adaptive algorithm 85.00 Azad [7] Fuzzy approach 89.00 Pieri et al [10] Matched filter 65.00 Ibrahimy et al [11] Statistical analysis 89.00 This research Artificial intelligence 93.75 and correlation…”
Section: Resultsmentioning
confidence: 99%
“…Therefore, the maternal contribution was not totally suppressed at the point in the FECG signal. [9] Adaptive algorithm 85.00 Azad [7] Fuzzy approach 89.00 Pieri et al [10] Matched filter 65.00 Ibrahimy et al [11] Statistical analysis 89.00 This research Artificial intelligence 93.75 and correlation…”
Section: Resultsmentioning
confidence: 99%
“…The interpretation of morphology, magnitude and frequency of fECG helps physicians to identify overall fetal health state [7]; however, the magnitude of fECG signals is usually overwhelmed by the magnitude of mECG signals, and significant frequency overlaps with other artifacts make the Signal to Noise Ratio (SNR) of the fECG signal very low. Therefore, advanced signal processing techniques are required for the extraction of fECG from the aECG signal [8].…”
Section: Introductionmentioning
confidence: 99%
“…Various techniques have been employed to address this problem, including digital filtering and cross-correlation with template [2], template subtraction [3], matched filtering [4], linear combination of phase difference corrected signals [5], independent component analysis (ICA) [6,7] and time-frequency analysis [8][9][10][11][12]. In this paper, an integrated approach for fetal heart beat detection is proposed, combining the Hilbert transform (HT) and non-linear state-space projections (NSSPs).…”
Section: Introductionmentioning
confidence: 99%