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A New Method for Foetal Electrocardiogram Extraction Using Adaptive Nero-Fuzzy Interference System Trained With PSO Algorithm

A New Method for Foetal Electrocardiogram Extraction Using Adaptive Nero-Fuzzy Interference System Trained With PSO Algorithm

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A New Method for Foetal Electrocardiogram Extraction Using Adaptive Nero-Fuzzy Interference System Trained With PSO Algorithm

†A new method for extracting the Foetal Electrocardiogram (FECG) signal form the two ECG signals recorded at the thoracic and abdominal areas of the motherís skin. The thoracic ECG is assumed to be completely maternal ECG (MECG) while the abdominal ECG is assumed to be a combination of motherís and foetusís ECG signals and random noise. The maternal component of the in the abdominal ECG is a nonlinearly transformed version of the MECG. The method uses Adaptive Nero-Fuzzy Inference System (ANFIS) structure for identifying 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. For synthetic signals, we have used a subjective criterion in addition to objective criteria. The results of extracting the FECG are promising comparing with conventional methods.



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  • Model: PROJ5684
  • 999 Units in Stock
  • Manufactured by: ClickMyProjects

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This product was added to our catalog on Tuesday 27 September, 2016.

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