Soft computing is a new approach to construct intelligent systems. The complex real world problems require intelligent systems that combine knowledge, techniques and methodologies from various sources. Neural networks recognize patterns and adapt themselves to cope with changing environments. Artificial neural network has potential applications in the field of ECG diagnosis measures. So noise reduced QRS complex of ECG signal is of utmost importance for automatic ECG interpretation and analysis. Noise is an unwanted energy, which interferes with the desired signal. Noise cancellation is mainly used as interference canceling in ECG, echo elimination on long distance telephone transmission lines and antenna side lobe interference canceling. In the study, the ECG signal is trained following various artificial neural network based algorithms to enhance the QRS complex by reducing noise for further analysis.
Dalal, Sambita and Sahoo, Laxmikanta
"ECG QRS Enhancement Using Artificial Neural Network,"
International Journal of Computer and Communication Technology: Vol. 1
, Article 4.
Available at: https://www.interscience.in/ijcct/vol1/iss3/4