ECG waveform analysis by significant point extraction. I. Data reduction
Computers and Biomedical Research
ECG waveform analysis by significant point extraction. II. Pattern Matching
Computers and Biomedical Research
Introduction to numerical analysis: 2nd edition
Introduction to numerical analysis: 2nd edition
A-to-D conversion from paper records with a desktop scanner and a microcomputer
Computers and Biomedical Research
C4.5: programs for machine learning
C4.5: programs for machine learning
Automatic detection of wave boundaries in multilead ECG signals: validation with the CSE database
Computers and Biomedical Research
Fuzzy modelling of the expert's knowledge in ECG-based ischaemia detection
Fuzzy Sets and Systems - Special issue on fuzzy signal processing
Cardia arrhythmia classification using neural networks
Technology and Health Care
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Digital Image Processing
Machine Learning
Bayes' Theorem Revised - The Rough Set View
Proceedings of the Joint JSAI 2001 Workshop on New Frontiers in Artificial Intelligence
The Rough Set View on Bayes' Theorem
AFSS '02 Proceedings of the 2002 AFSS International Conference on Fuzzy Systems. Calcutta: Advances in Soft Computing
Learning the Syntax and Semantic Rules of an ECG Grammar
AI*IA '97 Proceedings of the 5th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence
Syntactic recognition of ECG signals by attributed finite automata
Pattern Recognition
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An inference engine for classification of Electrocardiogram (ECG) signals is developed with the help of a rule based rough set decision system. For this purpose an automated data extraction system from ECG strips is being developed by using a few image processing techniques. A knowledge base is developed after consulting different medical books as well as feedback of reputed cardiologists on 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 rough set decision system is generated using these time-plane features for the development of an inference engine for disease classification. Two sets of rules are generated for this purpose. The first set is for general separation between normal and diseased subjects. The second set of rules is used for classifications between different diseases.