Title :
Combining neuro-fuzzy and chaos methods for intelligent time series analysis-case study of heart rate variability
Author :
Kozma, R. ; Kasabov, N.K. ; Swope, J.A. ; Williams, M.J.A.
Author_Institution :
Dept. of Inf. Sci., Otago Univ., Dunedin, New Zealand
Abstract :
The paper introduces a way of using chaos theory and a particular fuzzy neural network, called FuNN, for building adaptive, intelligent information systems. The use of the proposed connectionist-based methodology is illustrated through a biomedical application of heart rate variability (HRV) analysis. It is demonstrated that a multi-scale fractal analysis of HRV data can be used for characterisation and prediction of heart beat rhythms of patients with various cardiovascular disorders
Keywords :
cardiology; chaos; fractals; fuzzy neural nets; medical information systems; medical signal processing; patient care; patient monitoring; time series; FuNN; adaptive intelligent information system building; biomedical application; cardiovascular disorders; chaos theory; connectionist-based methodology; fuzzy neural network; heart beat rhythm characterisation; heart beat rhythm prediction; heart rate variability analysis; intelligent time series analysis; multi-scale fractal analysis; neuro-fuzzy method; patients; Adaptive systems; Chaos; Data analysis; Fractals; Fuzzy neural networks; Heart rate variability; Information systems; Intelligent networks; Intelligent structures; Intelligent systems;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.633050
