International Journal of Scientific and Research Publications

IJSRP, Volume 3, Issue 3, March 2013 Edition [ISSN 2250-3153]


A Novel Approach for Fetal ECG Extraction –Blood Pressure Patient Using Adaptive Neuro-Fuzzy Inference Systems Trained With PSO
      R.Anurekha, A.sivasankari
Abstract: Fetal ECG is an important parameter in medical field. Fetal Electrocardiogram (FECG) identifies the congenital heart problems at the earlier stage. Fetal Electrocardiogram (FECG) signal is extracted from blood pressure mothers abdomen. FECG signal is recorded at the thoracic and abdominal area of blood pressure mothers skin. The thoracic ECG is considered to be completely maternal ECG (MECG) of blood pressure mother. The abdominal ECG is considered to be a combination of blood pressure mother’s ECG signals and foetus ECG signals and random noise. The maternal component of abdominal ECG is a nonlinear transformed version of the Maternal ECG. The method Adaptive Neuro-Fuzzy Inference System (ANFIS) is used to identify the nonlinear transformation of maternal ECG. For identifying the nonlinear transformation and the FECG is extracted by subtracting the non linear version of the MECG signal from the abdominal ECG signal. ANFIS is trained with particle swarm optimization for better quality of signal. This method can be validated on both real and synthetic ECG signals. The results demonstrate the effectiveness of extracting the FECG from blood pressure mothers maternal ECG.

Reference this Research Paper (copy & paste below code):

R.Anurekha, A.sivasankari (2018); A Novel Approach for Fetal ECG Extraction –Blood Pressure Patient Using Adaptive Neuro-Fuzzy Inference Systems Trained With PSO; Int J Sci Res Publ 3(3) (ISSN: 2250-3153). http://www.ijsrp.org/research-paper-0313.php?rp=P15965
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