Automatic classification and robust identification

Authors: Atiyeh Ghoreyshi Henrietta Galiana

Publish Date: 2011/01/20

Volume: 31, Issue: 2, Pages: 347-368

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Abstract

The VestibuloOcular Reflex VOR stabilizes images of the world on our retinae when our head moves Basic daily activities are thus impaired if this reflex malfunctions During the past few decades scientists have modeled and identified this system mathematically to diagnose and treat VOR deficits However traditional methods do not analyze VOR data comprehensively because they disregard the switching nature of nystagmus this can bias estimates of VOR dynamics Here we propose for the first time an automated tool to analyze entire VOR responses slow and fast phases without a priori classification of nystagmus segments We have developed GNLHybELS Generalized NonLinear Hybrid Extended Least Squares an algorithmic tool to simultaneously classify and identify the responses of a multimode nonlinear system with delay such as the horizontal VOR and its alternating slow and fast phases This algorithm combines the procedures of Generalized Principle Component Analysis GPCA for classification and Hybrid Extended Least Squares HybELS for identification by minimizing a cost function in an optimization framework It is validated here on clean and noisy VOR simulations and then applied to clinical VOR tests on controls and patients Prediction errors were less than 1 deg for simulations and ranged from 69 deg to 21 deg for the clinical data Nonlinearities asymmetries and dynamic parameters were detected in normal and patient data in both fast and slow phases of the response This objective approach to VOR analysis now allows the design of more complex protocols for the testing of oculomotor and other hybrid systemsThis work was supported by a Discovery Grant from the Natural Sciences and Engineering Council NSERC Canada and the Canadian Institutes for Health Research CIHR Canada The authors are grateful to Dr A Katasarkas for his help in selecting and recruiting patient participation and to HL Smith for her assistance during clinical recordings

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