Research Article Open Access

Fetal Electrocardiogram Extraction Using Let Techniques

S. Hemajothi1 and K. Helen Prabha2
  • 1 St. Peter’s University, India
  • 2 RMD Engineering College, India


Fetal Electrocardiogram Extraction (FECG) identifies the congenital heart problems at the earlier stage. The major problem in the non invasive procedure is the extraction of FECG from Maternal ECG (MECG) and many interferences. The proposed methods (i) Combination of Adaptive Neuro Fuzzy Inference (ANFIS) and Fractional spline wavelet (ii) Combination of Fractional spline wavelet and ANFIS (iii) Combination of ANFIS and SURE-LET and (iv) Combination of SURE-LET and ANFIS remove the unwanted noises present in the FECG more effectively. This new approach extracts FECG by removing the noisy Abdominal ECG (AECG) and subsequently cancels the MECG. The pure thoracic ECG (TECG) or maternal ECG was used to remove noisy MECG present in the signal from abdomen signal and thereby the required noiseless FECG is extracted by means of the new approach. The excellence of the LET techniques are evaluated using Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). The result of combination of ANFIS and SURELET gives the best result and the closest match to the simulated FECG with high PSNR and low MSE among all the proposed methods.

Journal of Computer Science
Volume 8 No. 9, 2012, 1547-1553


Submitted On: 22 June 2012 Published On: 16 August 2012

How to Cite: Hemajothi, S. & Prabha, K. H. (2012). Fetal Electrocardiogram Extraction Using Let Techniques. Journal of Computer Science, 8(9), 1547-1553.

  • 1 Citations



  • Abdominal Electrocardiogram (AECG)
  • Adaptive Neuro-Fuzzy Inference System (ANFIS)
  • Fetal electrocardiogram (FECG)
  • Maternal Electro Cardiogram (MECG)
  • Mean Square Error (MSE)
  • Peak Signal to Noise Ratio (PSNR)