Abstract

This study proposes to achieve the affective assessment of a computer user through the processing of the pupil diameter (PD) signal. An adaptive interference canceller (AIC) system using the H∞ time-varying (HITV) adaptive algorithm was developed to minimize the impact of the PLR (pupil size changes caused by light intensity variations) on the measured pupil diameter signal. The modified pupil diameter (MPD) signal, obtained from the AIC, was expected to reflect primarily the pupillary affective responses (PAR) of the subject. Additional manipulations of the AIC output resulted in a Processed MPD (PMPD) signal, from which a classification feature, “PMPDmean”, was extracted. This feature was used to train and test a support vector machine (SVM), for the identification of “stress” states in the subject, achieving an accuracy rate of 77.78%. The advantages of affective recognition through the PD signal were verified by comparatively investigating the classification of “stress” and “relaxation” states through features derived from the simultaneously recorded galvanic skin response (GSR) and blood volume pulse (BVP) signals, with and without the PD feature. Encouraging results in affective assessment based on pupil diameter monitoring were obtained in spite of intermittent illumination increases purposely introduced during the experiments. Therefore, these results confirmed the possibility of using PD monitoring to evaluate the evolving affective states of a computer user.

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