Résumé : It has been shown that indecisiveness is involved in many
unwanted cognitive states, such as procrastination, distractibility,
the lack of self-esteem, or even revenge. The purpose of this work
is to propose a predictive model for the recognition of the
indecisiveness class, from the analysis of the customer’s
trajectory and his gripping. The movements are captured thanks
to infra-red sensors. A structural behavioral architecture is built,
based on eye-tracking methodology. Indeed, all the movements of
a customer in a selling area can be assimilated to fixations and
saccades. We show that the path in the selling area can be seen as
a sequence of states. The final predictive classifier is built with a
combination of Hidden Markov Models (HMM) through a
logistic regression model (LRM) and leads to satisfying results, as
it correctly predicts 88 % of the subjects’ indecisiveness classes.
