International Journal of Computer and Communication Technology IJCCT
ISSN: 2231-0371
Conference
Abstracting and Indexing
IJCCT
ECG QRS Enhancement Using Artificial Neural Network
Sambita Dalal
Department of Applied Electronics and Instrumentation Engineering ITER, S’O’A University Bhubaneswar, India
Laxmikanta Sahoo
Department of Applied Electronics and Instrumentation Engineering ITER, S’O’A University Bhubaneswar, India
Abstract
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.
Recommended Citation
[1] Saad Alshaban and Rawaa Ali, “Using neural network and fuzzy software for the classification of ECG Signals”. Research journal of applied sciences, Engineering and Technology 2(1): 5-10, 2010. ISSN: 2040-7467 Maxwell Scientific Organization, 2009. [2] Neural Network Toolbox 6 User’s Guide by Howard Demuth, Mark Beale and Martin Hagan. [3] Jamshid Nazari and Okan K. Ersoy “Implementation of backpropagation neural networks with MATLAB”. Electrical and Computer Engineering technical reports at Purdue Libraries in year 1992. [4] Alfonso “Application of artificial neural network for ECG signal detection and classification”, Journal of Electrocardiography, Vol 26 Supplement. [5] Thomas Murphy. “Explaining convolution using MATLAB”. [6] MATLAB The Language of Technical Computing, The Mathworks. [7] “Artificial Neural Networks” by Ajith Abraham. Chapter 29, pages 901 to 908. [8] “Implementing Artificial Neural Networks in MATLAB” by Sivanand. [9] G. Vijaya, V. Kumar and H.K. Verma, “ANN-based QRS complex analysis of ECG,” J. Med. Eng. Technol., vol. 22, no. 4, pp. 160-167, 1998. [10] “Kohonen T: Self-organization and associative memory”. SpringerVerlag. Berlin, 1984. [11] J.S.R.Jang, C.T.Sun and E.mizuatani, “Neuro-fuzzy and Soft computing”. Prentice Hall International Inc., 1997. [12] Martin T.Hagan, Howard B. Demuth, Mark Beale, “Neural network design”.