Comparison of Pupillary Light Reflex Sytem Modeling with H∞ and LSM Adaptive Algorithms

The pupillary light reflex (PLR), which decreases the pupil size as larger amounts of light are sensed by the retina, is considered as the dominant factor in determining the pupil size. However, it has been found recently that the pupil diameter (PD), controlled by the Autonomic Nervous System (ANS), also responds to cognitive and emotional processes. In this paper, we are interested in the modeling of the PLR system, so that the PD changes caused by light intensity variation can be distinguished from those due to affective stimuli. We tackle the modeling task with an adaptive interference canceller (AIC) architecture. We investigate the adaptation of the AIC using the popular least-mean-square (LMS) adaptation algorithm and the H-infinity time-varying algorithm. Preliminary results indicate that the latter algorithm seems better able to capture the PLR system dynamics.