Adaptive multiscale complexity analysis of fetal heart rate

Area of Science:

• Obstetrics and Gynecology
• Neonatal Medicine
• Biomedical Signal Processing

Background:

• Peripartum fetal asphyxia is a significant cause of neonatal morbidity and mortality.
• Fetal heart rate monitoring is crucial for early detection of acidosis, a key indicator of asphyxia.
• Existing methods may not fully address the non-stationary nature of fetal heart rate data during labor.

Purpose of the Study:

• To introduce a novel complexity analysis method for fetal heart rate (FHR) data.
• To evaluate the method's effectiveness in detecting fetal acidosis during labor.
• To assess the early detection capabilities and accuracy of the proposed approach.

Main Methods:

• Development of a novel complexity analysis technique using piecewise linear approximations of FHR data.
• The method is adaptive and multiscale, designed for the non-stationary context of labor.
• Validation using a reference dataset of real peripartum FHR data collected in situ.

Main Results:

• The proposed complexity analysis demonstrates promising performance in detecting fetal acidosis.
• Evaluated metrics include correct detection rates versus false detection rates and earliness of detection.
• Computational cost analysis indicates feasibility for clinical application.

Conclusions:

• The novel complexity analysis of FHR data shows significant potential for improving the detection of fetal asphyxia.
• This tool could enhance early identification of neonatal acidosis, reducing morbidity and mortality.
• MATLAB routines will be made available to facilitate further research and application.