An approach to a rough set based disease inference engine for ECG classification

Authors:
S. Mitra;M. Mitra;B. B. Chaudhuri
Affiliations:
Department of Applied Physics, Faculty of Technology, University of Calcutta, Kolkata, India;Department of Applied Physics, Faculty of Technology, University of Calcutta, Kolkata, India;Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata, India
Venue:
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
Year:
2006

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Abstract

An inference engine for classification of ECG signals is developed with the help of a rule based rough set decision system. For this purpose an automated ECG data extraction system from ECG strips is being developed by using few image processing techniques. Filtering techniques are used for removal of noises from recorded ECG. A knowledge base is developed after consultation of different medical books and feedback of reputed cardiologists regarding ECG interpretation and selection of essential time-plane features of ECG signal. An algorithm for extraction of different time domain features is also developed with the help of differentiation techniques and syntactic approaches. Finally, a rule-based roughest decision system is generated from these time-plane features for the development of an inference engine for disease classification.