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2 Biocybernetics and Biomedical Engineering

2 2013

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Improving fetal heart rate signal interpretation by application of myriad filtering

100%

Wróbel J. , Horoba K. , Pander T. , Jeżewski J. , Czabański R.

Biocybernetics and Biomedical Engineering

2013

tom Vol. 33, no. 4

211--221

Analysis of the fetal heart rate (FHR) signal is aimed at detection of clinically important patterns like bradycardia or tachycardia, accelerations and decelerations, as well as quantification of instantaneous FHR variability. Automated pattern recognition methods are based on estimation of so-called FHR baseline. It is a common opinion that the baseline estimation algorithm determines the efficiency of an entire process of quantitative signal analysis. Automated methods for baseline determination have been continuously improved for many years since there are still new classes of FHR signals being identified, for which the previous methods fail. The new method proposed for the baseline estimation is based on the weighted myriad filtering. The application of this method required filter parameter selection ensuring its operation according to clinical guidelines for baseline estimation. A very important feature of the myriad filtering is that there is no need for preliminary interpolation of signal loss segments. Our new algorithm was tested against two other methods. Thirty one-hour FHR recordings were selected for the analysis. Quantitative inconsistency was measured using differences between corresponding baseline samples. Additionally, the baselines were evaluated as regards their influence on identification of the acceleration and deceleration patterns. Obtained results allow us to conclude that the new algorithm delivers more reliable baselines particularly for signals with specific changes of the basal FHR level which has been recognized as difficult for baseline estimation.

Fetal state assessment using fuzzy analysis of fetal heart rate signals - Agreement with the neonatal outcome

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Czabański R. , Jeżewski J. , Horoba K. , Jeżewski M.

Biocybernetics and Biomedical Engineering

2013

tom Vol. 33, no. 3

145--155

Fetal monitoring is based on analysis of fetal heart rate signal. Visual interpretation is difficult so computer-aided systems for quantitative analysis are commonly used. The clinical interpretation guidelines provided by FIGO (Fédération Internationale de Gynécologie et d'Obstétrique) were used to develop the weighted fuzzy scoring system for qualitative assessment of the fetal state. In this work, agreement of the fuzzy classification system with the neonatal outcome assessment was analyzed. Various datasets were evaluated, depending on interpretation method of the signals which were recorded from patients. The obtained results confirmed possibility of the efficient fetal state assessment using the fuzzy inference method proposed.