Estimating Fetal Gestational Age Using Cardiac Valve Intervals

Marzbanrad, Faezeh; Khandoker, Ahsan H.; Kimura, Yoshitaka; Palaniswami, Marimuthu; Clifford, Gari D.

doi:10.22489/cinc.2016.035-146

Cited by 6 publications

(7 citation statements)

References 17 publications

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“…The authors would also like to thank the clinical support service team at Tohoku University for providing the fetal Doppler and fECG data. The current study extends our previous conference paper (Marzbanrad et al, 2016 ) by adding fECG and 1D-DUS signal quality assessment which improved the results, analysis of the results for different quality and fetal heart rate, and analysis for 30 additional cases with abnormalities.…”

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confidence: 62%

Assessment of Fetal Development Using Cardiac Valve Intervals

et al. 2017

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An automated method to assess the fetal physiological development is introduced which uses the component intervals between fetal cardiac valve timings and the Q-wave of fetal electrocardiogram (fECG). These intervals were estimated automatically from one-dimensional Doppler Ultrasound and noninvasive fECG. We hypothesize that the fetal growth can be estimated by the cardiac valve intervals. This hypothesis was evaluated by modeling the fetal development using the cardiac intervals and validating against the gold standard gestational age identified by Crown-Rump Length (CRL). Among the intervals, electromechanical delay time, isovolumic contraction time, ventricular filling time and their interactions were selected in a stepwise regression process that used gestational age as the target in a cohort of 57 fetuses. Compared with the gold standard age, the newly proposed regression model resulted in a mean absolute error of 3.8 weeks for all recordings and 2.7 weeks after excluding the low quality recordings. Since Fetal Heart Rate Variability (FHRV) has been proposed in the literature for assessing the fetal development, we compared the performance of gestational age estimation by our new valve-interval based method, vs. FHRV, while assuming the CRL as the gold standard. The valve interval-based method outperformed both the model based on FHRV. Results of evaluation for 30 abnormal cases showed that the new method is less affected by arrhythmias such as tachycardia and bradycardia compared to FHRV, however certain types of heart anomalies cause large errors (more than 10 weeks) with respect to the CRL-based gold standard age. Therefore, discrepancies between the regression based estimation and CRL age estimation could indicate the abnormalities. The cardiac valve intervals have been known to reflect the autonomic function. Therefore the new method potentially provides a novel approach for assessing the development of fetal autonomic nervous system, which may be growth curve independent.

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confidence: 62%

Assessment of Fetal Development Using Cardiac Valve Intervals

et al. 2017

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“…In earlier work, Marzbanrad et al ( 2016 ) estimated GA for 57 fetuses using a step-wise regression based on cardiac wall intervals derived from one-dimension Doppler ultrasound signal (1D-DUS) and fECG signals recorded in a Japanese hospital. The estimated GAs were compared to the GA derived from crown-rump length, achieving a mean square error of 3.8 and 5.1 weeks for cardiac intervals and fHRV parameters, respectively.…”

Section: Introductionmentioning

confidence: 99%

A Proxy for Detecting IUGR Based on Gestational Age Estimation in a Guatemalan Rural Population

Valderrama

Marzbanrad

Hall-Clifford

et al. 2020

Front. Artif. Intell.

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In-utero progress of fetal development is normally assessed through manual measurements taken from ultrasound images, requiring relatively expensive equipment and well-trained personnel. Such monitoring is therefore unavailable in low-and middle-income countries (LMICs), where most of the perinatal mortality and morbidity exists. The work presented here attempts to identify a proxy for IUGR, which is a significant contributor to perinatal death in LMICs, by determining gestational age (GA) from data derived from simple-to-use, low-cost one-dimensional Doppler ultrasound (1D-DUS) and blood pressure devices. A total of 114 paired 1D-DUS recordings and maternal blood pressure recordings were selected, based on previously described signal quality measures. The average length of 1D-DUS recording was 10.43 ± 1.41 min. The min/median/max systolic and diastolic maternal blood pressures were 79/102/121 and 50.5/63.5/78.5 mmHg, respectively. GA was estimated using features derived from the 1D-DUS and maternal blood pressure using a support vector regression (SVR) approach and GA based on the last menstrual period as a reference target. A total of 50 trials of 5-fold cross-validation were performed for feature selection. The final SVR model was retrained on the training data and then tested on a held-out set comprising 28 normal weight and 25 low birth weight (LBW) newborns. The mean absolute GA error with respect to the last menstrual period was found to be 0.72 and 1.01 months for the normal and LBW newborns, respectively. The mean error in the GA estimate was shown to be negatively correlated with the birth weight. Thus, if the estimated GA is lower than the (remembered) GA calculated from last menstruation, then this could be interpreted as a potential sign of IUGR associated with LBW, and referral and intervention may be necessary. The assessment system may, therefore, have an immediate impact if coupled with suitable intervention, such as nutritional supplementation. However, a prospective clinical trial is required to show the efficacy of such a metric in the detection of IUGR and the impact of the intervention.

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“…In addition, the recent availability of wireless fHR-monitoring systems [31] substantiates the fact that with using such technologies, it is now possible for pregnant women to move freely during their early stages of labor.…”

Section: Introductionmentioning

confidence: 99%

“…As the underlying physical principle used for abdominal ECG monitoring is not affected by the amount of maternal adipose tissue (body fat), the quality of the measured signal is quite high; therefore, abdominal electrocardiography is the only technique that potentially makes long-term ambulatory fetal monitoring possible. In addition, the recent availability of wireless fHR-monitoring systems [ 31 ] substantiates the fact that with using such technologies, it is now possible for pregnant women to move freely during their early stages of labor.…”

Section: Introductionmentioning

confidence: 99%

Non-Invasive Fetal Monitoring: A Maternal Surface ECG Electrode Placement-Based Novel Approach for Optimization of Adaptive Filter Control Parameters Using the LMS and RLS Algorithms

Martínek

Kahánková

Nazeran

et al. 2017

Sensors

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This paper is focused on the design, implementation and verification of a novel method for the optimization of the control parameters (such as step size μ and filter order N) of LMS and RLS adaptive filters used for noninvasive fetal monitoring. The optimization algorithm is driven by considering the ECG electrode positions on the maternal body surface in improving the performance of these adaptive filters. The main criterion for optimal parameter selection was the Signal-to-Noise Ratio (SNR). We conducted experiments using signals supplied by the latest version of our LabVIEW-Based Multi-Channel Non-Invasive Abdominal Maternal-Fetal Electrocardiogram Signal Generator, which provides the flexibility and capability of modeling the principal distribution of maternal/fetal ECGs in the human body. Our novel algorithm enabled us to find the optimal settings of the adaptive filters based on maternal surface ECG electrode placements. The experimental results further confirmed the theoretical assumption that the optimal settings of these adaptive filters are dependent on the ECG electrode positions on the maternal body, and therefore, we were able to achieve far better results than without the use of optimization. These improvements in turn could lead to a more accurate detection of fetal hypoxia. Consequently, our approach could offer the potential to be used in clinical practice to establish recommendations for standard electrode placement and find the optimal adaptive filter settings for extracting high quality fetal ECG signals for further processing. Ultimately, diagnostic-grade fetal ECG signals would ensure the reliable detection of fetal hypoxia.

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Estimating Fetal Gestational Age Using Cardiac Valve Intervals

Cited by 6 publications

References 17 publications

Assessment of Fetal Development Using Cardiac Valve Intervals

Assessment of Fetal Development Using Cardiac Valve Intervals

A Proxy for Detecting IUGR Based on Gestational Age Estimation in a Guatemalan Rural Population

Non-Invasive Fetal Monitoring: A Maternal Surface ECG Electrode Placement-Based Novel Approach for Optimization of Adaptive Filter Control Parameters Using the LMS and RLS Algorithms

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