Reducing sojourn points from recurrence plots to improve transition detection: Application to fetal heart rate transitions

Abstract

The analysis of biomedical signals demonstrating complexity through recurrence plots is challenging. Quantification of recurrences is often biased by sojourn points that hide dynamic transitions. To overcome this problem, time series have previously been embedded at high dimensions. However, no one has quantified the elimination of sojourn points and rate of detection, nor the enhancement of transition detection has been investigated. This paper reports our on-going efforts to improve the detection of dynamic transitions from logistic maps and fetal hearts by reducing sojourn points. Three signal-based recurrence plots were developed, i.e. embedded with specific settings, derivative-based and m-time pattern. Determinism, cross-determinism and percentage of reduced sojourn points were computed to detect transitions. For logistic maps, an increase of 50% and 34.3% in sensitivity of detection over alternatives was achieved by m-time pattern and embedded recurrence plots with specific settings, respectively, and with a 100% specificity. For fetal heart rates, embedded recurrence plots with specific settings provided the best performance, followed by derivative-based recurrence plot, then unembedded recurrence plot using the determinism parameter. The relative errors between healthy and distressed fetuses were 153%, 95% and 91%. More than 50% of sojourn points were eliminated, allowing better detection of heart transitions triggered by gaseous exchange factors. This could be significant in improving the diagnosis of fetal state.

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

“…The difference between the work we showcase in this paper and our previous work [3] is basically in the application part, the used RQA parameters and the mode of evaluating the discrimination. In Zaylaa et al [2,3] we have validated URPs on the logistic map and a single healthy and a single distressed fetuses.…”

“…Chen et al showed that RQA measures are more accurate than the standard entropy analysis techniques in detecting biomedical time series states [12]. Recurrence Plots introduced in our previous work [2,3] have shown their usefulness in detecting fetal distress due to IUGR. These plots were Unbiased Recurrence Plots (URPs) applied to Fetal Heart Rates (FHRs) in order to (i) validate the performance of the cuttingedge removal of sojourn points, i.e.…”

“…Some of these tools were quantitative, such as the entropy (En) analysis and types including, but not limited to, the approximated entropy, sample entropy, fuzzy entropy and recently n-order entropy [4,5,7,8,11]. Other methods were qualitative such as the Recurrence Plots (RPs) and their corresponding Recurrence Quantification Analysis (RQA) [2,3,10]. Chen et al showed that RQA measures are more accurate than the standard entropy analysis techniques in detecting biomedical time series states [12].…”

“…In Zaylaa et al [2,3] we have validated URPs on the logistic map and a single healthy and a single distressed fetuses. This paper demonstrates the application of URPs to a larger database composed of 50 FHRs (25 H-FHRs and 25 IUGR-FHRs).…”

“…Complexity analysis of fetal heart rate (FHR) recordings are constantly developed to discriminate distressed fetuses due to IUGR. Such complexity techniques have been employed to detect and classify signals into healthy and distressed classes [2][3][4][5][6][7][8][9][10].…”