Advanced Techniques in Biology & Medicine
Open Access

Abstract

Advanced Discrimination between Healthy and Intrauterine Growth Restricted Fetuses by Unbiased Recurrence Plots

Amira Zaylaa, Jamal Charara and Jean-Marc Girault

Intrauterine Growth Restriction, the poor growth of the fetus during pregnancy is a medical difficulty exposing the fetus to severe complications which could lead to its death. The discrimination of such medical problem is still challenging. This work aims to improve the discrimination between Intrauterine Growth Restricted fetuses from healthy fetuses, by comparing Unbiased Recurrence Plot analysis of their heart rates to standard recurrence plots. It also aims to offer the ultimate recurrence quantification parameter that leads the best discrimination. Entropy parameter, determinism, cross-determinism, recurrence rate and percentage of reduced sojourn points are computed from Unbiased Recurrence Plots. The evaluation of the effectiveness of discrimination is carried out using the sensitivity, specificity, accuracy and precision and Cohen’s kappa coefficient from the recurrence quantification analysis, and is compared to standard recurrence plots. Experimental results showed that the cross-determinism parameter is the utmost parameter providing a high discriminative power (86.5%) and the maximum relative separation between the two fetal heart rate sets (42.6%), and minimum standard deviation (± 0.12%). Both recurrence rate and entropy parameters are less active than cross-determinism but they are still adequate for Intrauterine Growth restricted fetuses classification. These results pave the way for highly sensitive classification devices. However, the detection of other medical problems should be further investigated, and deeper link of quantification parameters to distress diagnosis should be considered in order to understand the underlying physiological processes.