Title :
Suppression of maternal ECG from fetal ECG using neuro fuzzy logic technique
Author :
Vijila, C. Keri Selva ; Renganathan, S. ; Johnson, Stanley
Author_Institution :
Karunya Inst. of Technol., Coimbatore, 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. Neuro fuzzy is the combination of the neural network and fuzzy logic. Neural networks recognize patterns and adapt themselves to cope with changing environments. Fuzzy inference systems incorporate human knowledge and perform inferencing and decision making. Noise is an unwanted energy, which interferes with the desired signal. It can be suppressed with adaptive filters using signal processing. But if the noise frequency is same as the original signal then sometimes it also eliminates the desired signal. Therefore, noise cancellation is used which will not affect the desired signal. The basic principle of noise cancellation using neuro fuzzy is to filter out an interference component by identifying the nonlinear model between a measurable interference (J.S.R. Jang, et al., 1997). The matlab command called ´ANFIS´ (adaptive neuro fuzzy inference system) is used to demonstrate how noise cancellation can be applied as interference canceling in ECG [Fuzzy logic tool box].
Keywords :
adaptive filters; electrocardiography; fuzzy logic; fuzzy neural nets; inference mechanisms; interference suppression; medical signal processing; pattern recognition; Soft computing; adaptive filters; adaptive neuro fuzzy inference system; decision making; fetal ECG; fuzzy inference systems; inferencing; intelligent systems; interference canceling; maternal ECG; matlab; neuro fuzzy logic technique; noise cancellation; noise frequency; pattern recognition; signal processing; Electrocardiography; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Intelligent systems; Interference; Neural networks; Noise cancellation; Pattern recognition; Working environment noise;
Conference_Titel :
Neural Networks, 2003. Proceedings of the International Joint Conference on
Print_ISBN :
0-7803-7898-9
DOI :
10.1109/IJCNN.2003.1223828