Fetal Heart Rate Preprocessing Techniques: A Scoping Review

Area of Science:

• Medical Signal Processing
• Obstetrics and Gynecology
• Biomedical Engineering

Background:

• Fetal heart rate (FHR) monitoring via cardiotocography is critical for detecting fetal distress and guiding obstetric interventions.
• FHR signals frequently contain artifacts and noise, necessitating robust preprocessing for accurate clinical interpretation.
• Existing research lacks standardized methodologies for FHR signal preprocessing, impacting diagnostic reliability.

Purpose of the Study:

• To systematically review and synthesize preprocessing techniques applied to human FHR signals.
• To identify prevalent methods for detecting and correcting poor signal quality in FHR data.
• To highlight the lack of consensus on artifact and outlier definitions in FHR signal analysis.

Main Methods:

• A scoping review adhering to PRISMA-ScR guidelines was conducted.
• Literature search performed on PubMed and Web of Science databases for articles on FHR signal preprocessing up to May 2021.
• Included 54 original research articles from an initial 322 identified unique articles.

Main Results:

• Preprocessing approaches primarily focused on identifying and rectifying signal quality issues.
• Signal quality detection commonly involved analyzing deviations from adjacent data points.
• Interpolation techniques were frequently employed for signal correction.
• A significant lack of agreement exists regarding the definitions of missing data, outliers, and artifacts.

Conclusions:

• There is a growing research interest in FHR signal preprocessing, particularly between 2011 and 2021.
• Standardization of FHR signal preprocessing methods is essential to improve diagnostic accuracy.
• Future research should evaluate and refine preprocessing techniques across diverse FHR datasets to enhance their effectiveness.