A new method for extraction of fetal electrocardiogram signal based on Adaptive Nero-Fuzzy Inference System

This paper proposes a new method for extracting the Foetal Electrocardiogram (FECG) signal from two ECG signals recorded at thoracic and abdominal areas of mother. The thoracic ECG is assumed to be completely maternal ECG (MECG) while the abdominal ECG is assumed to be a combination of mother's and fetus's ECG signals and random noise. The maternal component of the abdominal ECG is a nonlinearly transformed version of MECG. The method uses Adaptive Nero-Fuzzy Inference System (ANFIS) structure to identify the nonlinear transformation. We have used Particle Swarm Optimization (PSO) as a new tool for training the ANFIS structure. By identifying the nonlinear transformation, we have extracted FECG by subtracting the aligned version of the MECG signal from the abdominal ECG (AECG) signal. We validate our new method on both real and synthetic ECG signals. The results shows improvement in extraction of foetal electrocardiogram signal with our proposed method.