A Real-Time Intrauterine Catheter Technique for Fetal Electrocardiogram Monitoring

Abstract

A fetal eletrocardiogram (FECC) obtained via an intrauterine catheter (IC) is a compromise between the clinically accepted invasive scalp electrode, and the non-invasive abdominal wall approaches, The catheter is inserted into the uterus during delivery, but is non-invasive to the fetus, The IC can be modified to contain a pressure sensor to monitor contractions, The modified IC would enable fetal heart rate and contractions to be monitored with one sensor, Currenfly, two sensors that include the invasive scalp electrode and intrauterine pressure catheter are used clink ally, Signal processing is required to obtain a FECG via the IC, Usually the maternal electrocardiogram (ECG) is present in the IC's signal along with electromyographic noise, Obtaining the FECG in real-time further complicates the processing since the FECG can be similar in amplitude to the maternal ECG, Current techniques for maternal ECG cancellation produce a significant residual during the initial processing of the algorilhm and/or falsely detect the FECG for the maternal ECG, A real-time IC technique will be discussed, The results from clinical data from eight patients indicate a FECG with a good signal-to-noise ratio can be obtained even during the first seconds and minutes of operation,

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA409184

Entities

People

  • S. L. Horner
  • W. M. Holls

Organizations

  • Bucknell University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Abdomen
  • Algorithms
  • Bandpass Filters
  • Cancellation
  • Catheters
  • Data Acquisition
  • Digital Signal Processing
  • Electrical Engineering
  • Electrocardiography
  • Electrodes
  • Engineering
  • Heart
  • Heart Rate
  • Low Noise
  • Monitoring
  • Noise
  • Signal Processing

Fields of Study

  • Medicine

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Women's Health and Cancer Risk Research: African American Women and Pregnancy Outcomes.