Parameters optimization using genetic algorithm technique for Vestibulo-ocular reflex model

The Vestibulo-ocular reflex (VOR) model proposed by Merfeld and Zupan (2002) has been used in a wide number of medical applications as well as the driver behavior model. This model is one of the reflex eye movements. It can deal with the interaction between the otolith and the semicircular canal with four parameters to compensate for the individual difference of the VOR characteristics and two parameters to compensate for that of the eye muscle characteristics. In order to increase the reliability, exact ability of this model, by using genetic algorithm (GA) the parameters were identified base on the result of experiment and simulation. We conducted 12 experiments with the motion capture and the eye movement equipment. The new parameters identified by the new GA technique improved simulation results compares with Merfeld parameters and the previous GA method by applying the generating near optimal initial population and changing fitness function. The range of each parameter on VOR model was identified with main purpose to choose the best parameters for each model application. We developed a Matlab toolbox for identifying parameter base on Matlab Graphical User Interfaces.