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Related Experiment Video

Updated: Sep 7, 2025

Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation
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Heart rate estimation and validation algorithm for fetal phonocardiography.

Amrutha Bhaskaran1, Sidhesh Kumar J1, Shirley George2

  • 1Indian Institute of Science (IISc), Bangalore, India.

Physiological Measurement
|June 20, 2022
PubMed
Summary
This summary is machine-generated.

This study developed an automatic algorithm for fetal heart rate (FHR) detection from heart sounds, improving accuracy in noisy environments. The validated algorithm significantly reduced errors, offering a promising non-invasive monitoring method.

Keywords:
FHRautocorrelationenvelope detectionfetal heart sound

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Area of Science:

  • Biomedical Engineering
  • Maternal-Fetal Medicine
  • Signal Processing

Background:

  • Fetal heart rate (FHR) monitoring is crucial for assessing fetal well-being.
  • Doppler ultrasound is the standard FHR measurement method.
  • Fetal phonocardiography offers a non-invasive, passive alternative, but requires reliable algorithms for noisy environments.

Purpose of the Study:

  • To develop and validate an automatic algorithm for determining FHR from fetal heart sound recordings.
  • To assess the algorithm's performance in noisy clinical settings.
  • To evaluate the algorithm's accuracy and reliability using Mean Absolute Error (MAE) and positive percent agreement.

Main Methods:

  • Fetal heart sounds were recorded using an electronic stethoscope from 30-40 weeks of gestation.
  • An algorithm combining envelope detection and autocorrelation was developed.
  • Peak validation using prior FHR data and power spectral density refined algorithm accuracy.

Main Results:

  • The algorithm's Mean Absolute Error (MAE) decreased from 11.50 to 7.54 beats per minute after implementing the validation step.
  • Positive percent agreement improved from 81% to 87% with the validation.
  • Algorithm performance was analyzed across recordings classified as good, moderate, and poor quality.

Conclusions:

  • The proposed algorithm provides accurate FHR measurements, especially after validation.
  • The algorithm demonstrates potential as a non-invasive fetal monitoring tool.
  • Algorithm accuracy is influenced by environmental noise, highlighting the importance of signal quality.