A Non-intrusive Single Channel Abdominal Fetal Electrocardiogram Monitor Using Singular Value Decomposition

• Main Authors: Rodriguez, Richmond Roi B, Mapolon, Ruby Jane A, Reyes, Rosula SJ
• Format: text
• Published: Archīum Ateneo 2021
• Subjects: pregnancy; hospitals; signal processing algorithms; electrocardiography; signal processing; data mining; sustainable development; Fetal electrocardiogram; filtering; monitoring system; SVD; Fetal ECG Extraction; Analytical, Diagnostic and Therapeutic Techniques and Equipment; Biomedical; Electrical and Computer Engineering; Maternal, Child Health and Neonatal Nursing
• Online Access: https://archium.ateneo.edu/ecce-faculty-pubs/125; https://ieeexplore.ieee.org/document/9664665
• Institution: Ateneo De Manila University

The maternal mortality rate (MMR) in the country is at 100 maternal deaths per 100,000 live births, which falls short from the Sustainable Development global goal of 70 maternal deaths per 100,000 live births. Current devices used to monitor fetal health are stationed at big hospitals, inaccessible to those living in remote areas. In this study, MAX-ECG-MONITOR, a device for collecting ECG signals, was used to develop a mobile application for fetal electrocardiogram (fECG) monitoring system. The signals gathered will be processed first through Singular Value Decomposition. The signal processing consists of three fundamental steps: estimation of maternal electrocardiogram (mECG), subtraction of maternal component from the waveforms, and extraction of fECG from the remaining signal. The signal processing was validated using a testing framework for the fetal ECG extraction algorithm. The program showed accuracy above 90 percent for signals with and without noise.