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The monitoring and diagnosis of uterine electrical activity, specifically in distinguishing between term and preterm labor, greatly relies on the modeling and evaluation of electrohysterogram signals (EHG). It is widely acknowledged that fractional systems can accurately imitate a large range of physical occurrences. This article aims to develop a methodology for classifying pre-term labor using a fractional order system model. The parameters of the proposed fractional order model will be derived from the EHG signals through an innovative fractional identification technique. To validate the modeling approach, 300 records from the Term-Preterm EHG Database TPEHG database.

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Premature Labor Detection Based on Fractional Order System Modeling

  • 会议论文

  • 发表日期：

    2025年

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  • Imen Assadi,
  • Tahar Bensouici

摘要

The monitoring and diagnosis of uterine electrical activity, specifically in distinguishing between term and preterm labor, greatly relies on the modeling and evaluation of electrohysterogram signals (EHG). It is widely acknowledged that fractional systems can accurately imitate a large range of physical occurrences. This article aims to develop a methodology for classifying pre-term labor using a fractional order system model. The parameters of the proposed fractional order model will be derived from the EHG signals through an innovative fractional identification technique. To validate the modeling approach, 300 records from the Term-Preterm EHG Database TPEHG database.