Title: Modelling of dynamic cerebral pressure autoregulation using sequential genetic algorithm

Authors: Shiru Sharma, Ranjana Patnaik, Neeraj Sharma, J.P. Tiwari

Addresses: School of Biomedical Engineering, Institute of Technology, Banaras Hindu University, Varanasi 221 005, UP, India. ' School of Biomedical Engineering, Institute of Technology, Banaras Hindu University, Varanasi 221 005, UP, India. ' School of Biomedical Engineering, Institute of Technology, Banaras Hindu University, Varanasi 221 005, UP, India. ' Department of Electrical Engineering, Institute of Technology, Banaras Hindu University, Varanasi, 221 005, UP, India

Abstract: Accurate modelling is desirable for analysis and clinical studies of physiological systems. The present work provides methodology for fully automated sequential genetic algorithm (SGA) for auto regressive exogenous (ARX) modelling. The SGA has been implemented to determine proper model structure and thereafter model parameters. The proposed algorithm has been tested on known ARX model and sunspot data modelling problem. Finally, SGA has been applied to model the dynamic cerebral autoregulation (CA) system. The results are promising and models obtained using SGA are better as compared to standard least square (LS) algorithms and can be reliably applied to model physiological system.

Keywords: genetic algorithms; sequential QAs; system identification; ARX models; model structure; cerebral autoregulation; mathematical modelling; autoregressive exogenous models; physiological systems; arterial blood pressure; ABP; cerebral blood flow velocity; CBFV; cerebral pressure autoregulation.

DOI: 10.1504/IJMMNO.2010.035428

International Journal of Mathematical Modelling and Numerical Optimisation, 2010 Vol.1 No.4, pp.299 - 315

Published online: 30 Sep 2010 *

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