Krzysztof Horoba

Quantitative analysis of contraction patterns in electrical activity signal of pregnant uterus as an alternative to mechanical approach

Monitoring of uterine contraction activity is an important diagnostic tool used during both pregnancy and labour. The strain the pregnant uterus exerts on the maternal abdomen is measured via external tocography. However, limitation of this approach has caused the development of another technique-electrohysterography--which is based on the recording of electrical uterine activity. A computer-aided system is presented, which allows the recording of electrohysterographic signals from the maternal abdomen and their on-line analysis both in time and frequency domains. As a research material, we acquired 108 traces during a 24 h period before labour from a group of patients between 37 and 40 weeks of gestation. The comparison study between electrohysterography and tocography was carried out thanks to the possibility of simultaneous recording of mechanical and electrical uterine activities. The obtained results show that both methods demonstrate high agreement in relation to the number of contractions recognized as being consistent. However, their agreement in relation to the quantitative description of recognized patterns has appeared to be unacceptable to consider these methods as fully alternative. The appropriate way of further development of electrohysterography seems to be spectral analysis. Several spectral parameters describing electrophysiological properties of uterine muscle can be obtained by the use of electrohysterographic signals.

Comparison of Doppler ultrasound and direct electrocardiography acquisition techniques for quantification of fetal heart rate variability

A method for comparison of two acquisition techniques that are applied in clinical practice to provide information on fetal condition is presented. The aim of this work was to evaluate the commonly used Doppler ultrasound technique for monitoring of mechanical activity of fetal heart. Accuracy of beat-to-beat interval determination together with its influence on indices describing the fetal heart rate (FHR) variability calculated automatically using computer-aided fetal monitoring system were examined. We considered the direct fetal electrocardiography as a reference technique because it ensures the highest possible accuracy of heart interval measurement, and additionally all the definitions of popular time domain parameters quantifying FHR variability formerly have been created using the fetal electrocardiogram. We evaluated the reliability of various so called short-term and long-term variability indices, when they are calculated automatically using the signal obtained via the Doppler US from a fetal monitor. The results proved that evaluation of the acquisition technique influence on fetal well-being assessment cannot be accomplished basing on direct measurements of heartbeats only. The more relevant is the estimation of accuracy of the variability indices, since analysis of their changes can significantly increase predictability of fetal distress

A novel technique for fetal heart rate estimation from Doppler ultrasound signal

BackgroundThe currently used fetal monitoring instrumentation that is based on Doppler ultrasound technique provides the fetal heart rate (FHR) signal with limited accuracy. It is particularly noticeable as significant decrease of clinically important feature - the variability of FHR signal. The aim of our work was to develop a novel efficient technique for processing of the ultrasound signal, which could estimate the cardiac cycle duration with accuracy comparable to a direct electrocardiography.MethodsWe have proposed a new technique which provides the true beat-to-beat values of the FHR signal through multiple measurement of a given cardiac cycle in the ultrasound signal. The method consists in three steps: the dynamic adjustment of autocorrelation window, the adaptive autocorrelation peak detection and determination of beat-to-beat intervals. The estimated fetal heart rate values and calculated indices describing variability of FHR, were compared to the reference data obtained from the direct fetal electrocardiogram, as well as to another method for FHR estimation.ResultsThe results revealed that our method increases the accuracy in comparison to currently used fetal monitoring instrumentation, and thus enables to calculate reliable parameters describing the variability of FHR. Relating these results to the other method for FHR estimation we showed that in our approach a much lower number of measured cardiac cycles was rejected as being invalid.ConclusionsThe proposed method for fetal heart rate determination on a beat-to-beat basis offers a high accuracy of the heart interval measurement enabling reliable quantitative assessment of the FHR variability, at the same time reducing the number of invalid cardiac cycle measurements.

Predicting the Risk of Low-Fetal Birth Weight From Cardiotocographic Signals Using ANBLIR System With Deterministic Annealing and

Cardiotocography (CTG) is a biophysical method of fetal condition assessment based mainly on recording and automated analysis of fetal heart activity. The computerized fetal monitoring systems provide the quantitative description of the CTG signals, but the effective conclusion generation methods for decision process support are still needed. Assessment of the fetal state can be verified only after delivery using the fetal (newborn) outcome data. One of the most important features defining the abnormal fetal outcome is low birth weight. This paper describes an application of the artificial neural network based on logical interpretation of fuzzy if-then rules neurofuzzy system to evaluate the risk of low-fetal birth weight using the quantitative description of CTG signals. We applied different learning procedures integrating least squares method, deterministic annealing (DA) algorithm, and ε-insensitive learning, as well as various methods of input dataset modification. The performance was evaluated with the number of correctly classified cases (CC) expressed as the percentage of the testing set size, and with overall index (OI) being the function of predictive indexes. The best classification efficiency (CC = 97.5% and OI = 82.7%), was achieved for integrated DA with ε-insensitive learning and dataset comprising of the CTG traces recorded as earliest for a given patient. The obtained results confirm efficiency for supporting the fetal outcome prediction using the proposed methods.

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Bioelectrical fetal heart activity being recorded from maternal abdominal surface contains more information than mechanical heart activity measurement based on the Doppler ultrasound signals. However, it requires extraction of fetal electrocardiogram from abdominal signals where the maternal electrocardiogram is dominant. The simplest technique for maternal component suppression is a blanking procedure, which relies upon the replacement of maternal QRS complexes by isoline values. Although, in case of coincidence of fetal and maternal QRS complexes, it causes a loss of information on fetal heart activity. Its influence on determination of fetal heart rate and the variability analysis depends on the sensitivity of the heart-beat detector used. The sensitivity is defined as an ability to detect the incomplete fetal QRS complex. The aim of this work was to evaluate the influence of the maternal electrocardiogram suppression method used on the reliability of FHR signal being calculated.

-Insensitive Learning

Among various methods of monitoring fetal heart activity a Doppler ultrasound technique is the most often used. Complexity and variability of Doppler signal make difficult the precise measurement of timing dependences defining individual phases of cardiac cycle. Aim of the work was to carry out detailed comparative analysis of Doppler echo coming from movement of two different objects within fetal heart: valve and wall. Joint time frequency analysis were applied. Fetal monitor performed a role of input device in our measurement station based on LabView environment. Doppler signal was acquired from analog outputs with a help of dedicated data acquisition card. Average recording time in a group of 15 patients was 20 minutes. Analysis comprised determination and comparison of spectrograms and power density spectrums corresponding to individual phases of cardiac cycle.

The influence of coincidence of fetal and maternal QRS complexes on fetal heart rate reliability

Analysis of variability of fetal heart rate (FHR) is very important in prediction of the fetal wellbeing. The beat-to-beat variability is described quantitatively by the indices originated from invasive fetal electrocardiography which provides the FHR signal in a form of time event series. Today, monitoring instrumentation is based on Doppler ultrasound technology. We used two bedside fetal monitors with different processing methods for heartbeat detection and FHR signal determination: the autocorrelation and cross-correlation techniques. Both monitors provide the output signal in a form of evenly spaced samples. The goal of this paper is to present a new method for the FHR signal processing, which enables extraction of series of consecutive heartbeat intervals from the sampled signal. The proposed correction algorithms allow recognition and removal of the FHR signal distortions typical for fetal monitors-invalid and duplicated samples. The correction efficiency has been verified based on the FHR variability indices calculated for the sampled signal and the corresponding event series. For both monitors, considerable influence of the signal representation on indices values was noted. Concluding, we recommended implementing these algorithms in fetal surveillance system as a preprocessing stage for the determination of FHR variability indices.

Timing events in Doppler ultrasound signal of fetal heart activity

In this paper we propose a new structure of the instrumentation for electrocardiographic fetal monitoring. We apply a single-channel approach to maternal electrocardiogram suppression in the recorded four abdominal bioelectric signals. Then we exploit spatial and temporal properties of the extracted four-channel fetal electrocardiogram to construct a new channel with higher signal-to-noise ratio. Finally, we perform detection of fetal QRS complexes. The proposed approach is investigated with the help of the constructed database of the maternal abdominal signals. During the detection tests, the spatio-temporal filtering allowed us to decrease significantly the number of the detection errors of different detectors applied. Moreover, we present visually that even if the fetal QRS complexes are buried in noise, the spatio-temporal filtering can produce the signal with the discernible ones.

Extraction of Fetal Heart-Rate Signal as the Time Event Series From Evenly Sampled Data Acquired Using Doppler Ultrasound Technique

At present, the most widespread method of monitoring uterine contractions activity during pregnancy and labour is the external tocography method. This mechanical method, however, has limited value resulting from its low accuracy and sensibility. Recent progress in new techniques of perinatal monitoring requires a more precise method of monitoring uterine activity. The most promising seems to be electrohysterography, which consists in the recording of electrical uterine activity by means of electrodes attached to abdominal wall. We made an attempt to evaluate the possibility to replace the traditional mechanical method by this electrical one. We developed methods of extraction of the slow wave from an electrohysterogram. This slow wave corresponds to mechanical signal and can be regarded as a contractions wave. Then, using this wave, the contractions detection can be performed in a similar way as in a conventional tocogram. The results obtained allow one to conclude that there is a close relation between the electrical and mechanical signals of uterine activity. It is manifested by a similar number of contractions detected and a large number of contractions being consistent.

Application of spatio-temporal filtering to fetal electrocardiogram enhancement

Cardiotocographic monitoring is a primary biophysical method for assessment of a fetal state based on quantitative analysis of the biophysical signals. Although the computerized fetal monitoring systems have become a standard in clinical centres, the effective methods, which could enable conclusion generation, are still being searched. In the proposed work the attempts have been made to answer some important questions, which occurred during application of neural network for classification of the fetal state as being normal or abnormal. These questions are particularly important for medical applications and concern the influence of data set organization, inputs representation and the networks architecture. The networks of MLP and RBF types were developed and tested using 50 trials, with randomly mixed data contents in learning, validating and testing subsets. Additionally, the influence of numerical and categorical representation of the input quantitative parameters describing fetal cardiotocograms on the efficiency of the learning process was tested.