A Neural-Network-Based Eye Pupil Reaction Model for Use with Television Programs

Abstract

If the effects of variations in brightness can be controlled, it is possible to use changes in pupil size for the evaluation of educational TV programs. This paper describes an improved, neural-network-based method for studying pupil reactions and the feasibility of evaluating TV programs by investigating changes in pupil size. This neural-network pupil reaction model uses M-sequences and Markov-sequences to register changes in pupil size based upon responses to changes in brightness, and this paper shows it to be more effective in removing the effects of brightness on pupil size than other previously reported methods. The authors also discuss methods for removing the influence of brightness from pupil response, as well as methods for evaluating changes in pupil size. It is also shown that this new method permits the objective evaluation of TV programs through the measurement of changes in pupil size while viewing TV programs.