ID 2363: Smartwatch-Enhanced Pregnancy Monitoring: ECG Analysis for Gestational Age Estimation

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Master’s Thesis / Research Internship / Project

Pregnancy is a multifaceted process marked by physiological changes in the female body. Electrocardiogram (ECG) patterns also evolve during pregnancy, adapting to the demands of this transformative phase. With modern smartwatches, wrist-worn ECG monitoring has become accessible. Yet, the capacity of these devices to capture pregnancy-related ECG variations, particularly their utility in estimating gestational age, remains uncertain. This research examines the feasibility of using smartwatches to monitor pregnancy and assess dynamic ECG changes, with the potential to serve as a supportive tool for determining pregnancy week in the future.


  • Conducting a comprehensive literature review to identify ECG parameters that exhibit changes during pregnancy.
  • Extraction of relevant ECG parameters from a large dataset.
  • Analysis of relevant ECG parameters throughout the stages of pregnancy to discern patterns and variations.


  • Basic knowledge in biomedical signal processing and big data handling
  • Strong interest in mobile health topics and wearable devices


Katharina Jäger, M. Sc.

Researcher & PhD Candidate

Michael Nissen, M. Sc.

Researcher & PhD Candidate