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Passive Fetal Movement Signal Detection System Based on Intelligent Sensing Technology.
Sensong Liang1, Jiansheng Peng1,2, Yong Xu2
1Department of Electronic Engineering, Guangxi Normal University, Guilin, China.
Journal of Healthcare Engineering
|September 20, 2021
Summary
This study introduces a novel system for detecting fetal movement (FM) signals using intelligent sensing. The new method improves FM signal identification and classification, offering promise for wearable fetal health monitoring.
Area of Science:
- Biomedical Engineering
- Signal Processing
- Maternal-Fetal Medicine
Background:
- Fetal movement (FM) is crucial for assessing fetal health.
- Traditional methods struggle with accurate FM signal extraction and recognition.
- Intelligent sensing technology offers a potential solution for improved FM detection.
Purpose of the Study:
- To develop a passive FM signal detection system using intelligent sensing technology.
- To overcome challenges in FM signal extraction and improve recognition rates.
- To enhance the accuracy of fetal health monitoring through advanced signal processing.
Main Methods:
- Utilized accelerometers to capture FM signals from the maternal abdomen.
- Implemented Kalman filtering for FM signal reconstruction amidst noise.
- Employed dictionary learning, orthogonal matching pursuit, and adaptive filtering for signal identification.
- Applied mask fusion classification based on multi-axis recognition results.
Main Results:
- The developed system demonstrated effective FM signal detection and classification.
- Orthogonal matching pursuit outperformed adaptive filtering in FM signal identification, achieving an 89.74% positive prediction value.
- The system successfully processed both public and self-built accelerated FM datasets.
Conclusions:
- The proposed intelligent sensing system offers a promising approach for passive FM signal detection.
- The system shows potential for future wearable FM health monitoring applications.
- Advanced signal processing techniques significantly improve the accuracy of FM detection.
