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Fetal Electrocardiogram Extraction and Analysis Using Adaptive Noise Cancellation and Wavelet Transformation
1Department of Biomedical Engineering, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India. sutharvs@gmail.com.
Journal of Medical Systems
|December 10, 2017
Summary
Continuous fetal ECG monitoring is crucial for early detection of birth defects. This study developed a portable device and signal processing algorithms to extract fetal ECG from maternal ECG, enabling long-term monitoring and analysis of fetal heart rate variability.
Area of Science:
- Biomedical Engineering
- Cardiology
- Signal Processing
Background:
- Congenital heart defects are a leading cause of birth defect-related mortality.
- Current fetal monitoring methods like Cardiotachography (CTG) are limited for long-term, continuous use.
- Non-invasive fetal electrocardiogram (fECG) monitoring is essential for early detection of fetal cardiac issues.
Purpose of the Study:
- To develop a portable hardware prototype for continuous fetal ECG monitoring.
- To implement and evaluate signal processing algorithms for extracting fECG from maternal ECG.
- To analyze fetal heart rate variability (HRV) for assessing fetal health status.
Main Methods:
- Designed and developed a prototype hardware for raw ECG signal acquisition.
- Employed two signal processing techniques: Least Mean Square (LMS) adaptive noise cancellation and Wavelet Transformation.
- Evaluated algorithms using simulated, database, and subject-acquired ECG signals.
Main Results:
- Successfully extracted fetal ECG signals using both LMS and Wavelet methods.
- Achieved high sensitivity and accuracy for fetal QRS detection (Adaptive: 96.83% sensitivity, 89.87% accuracy; Wavelet: 95.97% sensitivity, 88.5% accuracy).
- Analyzed time-domain parameters of fetal and maternal heart rate variability.
Conclusions:
- The developed prototype and signal processing algorithms enable effective continuous non-invasive fetal ECG monitoring.
- Both LMS and Wavelet techniques are viable for fECG extraction and HRV analysis.
- This approach supports early identification of fetal health issues and can aid in preventing stillbirths.
