Title :
ECG diagnosis using neural network and fuzzy expert system
Author :
Sivathasan, S. ; Cecelja, F. ; Balachandran, W.
Author_Institution :
Dept. of Syst. Eng., Brunel Univ., Uxbridge, UK
Abstract :
The aim of this research is to develop an intelligent diagnostic system to be used in the coronary care unit (CCU) for both optimal therapy and clinical research. The system will have the abilities to detect, analyse, interpret, intervene, code and store all modifications in the input streams of the electrical signals which reflect a significant change in the patients physiological state using retrospective case history analysis. The novelty of this research is to use the artificial neural network as a classifier and fuzzy expert system for the final diagnostic decision
Keywords :
diagnostic expert systems; electrocardiography; fuzzy neural nets; medical diagnostic computing; signal classification; ECG diagnosis; artificial neural network; classifier; clinical research; coronary care unit; fuzzy expert system; intelligent diagnostic system; neural network; optimal therapy; patients physiological state; retrospective case history analysis; Artificial intelligence; Artificial neural networks; Diagnostic expert systems; Electrocardiography; Expert systems; Hybrid intelligent systems; Medical treatment; Neural networks; Signal analysis; Signal processing;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 2000. IMTC 2000. Proceedings of the 17th IEEE
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-5890-2
DOI :
10.1109/IMTC.2000.848889
