Dynamic smooth pursuit gain estimation from eye tracking data

The smooth pursuit gain (SPG) is defined as the ratio of the angular velocity of the eye to that of the moving target. Being evaluated at a certain frequency of harmonic visual stimuli, it has been widely used in medicine as a measure of oculomotor system performance. In this study, the smooth pursuit system (SPS) is modeled as a dynamical system whose output signal is the angular velocity of the eye and the input is the angular velocity of a moving stimulus. Then, by means of system identification, the entire dynamics of SPS can be estimated, provided the visual stimuli are properly designed. This technique is referred to as the dynamic SPG (DSPG). Systems appearing equivalent in terms of SPG, can therefore be distinguished between using DSPG. Modern eye tracking techniques register gaze direction over time, but do not measure gaze velocity. Hence, to estimate the SPG/DSPG, differentiation must be applied to the output of the eye tracker. Four approaches to differentiation of eye-tracking data are evaluated in this paper with respect to the estimation of DSPG, out of which the method based on Laguerre functions stands out as the most reliable technique for this particular application.