Learning and Generalization in Haptic Classification of 2-D Raised-Line Drawings of Facial Expressions of Emotion by Sighted and Adventitiously Blind Observers

Abstract

Sighted blindfolded individuals can successfully classify basic facial expressions of emotion (FEEs) by manually exploring simple 2-D raised-line drawings (Lederman et al 2008, IEEE Transactions on Haptics1 27–38). The effect of training on classification accuracy was assessed by sixty sighted blindfolded participants (experiment 1) and by three adventitiously blind participants (experiment 2). We further investigated whether the underlying learning process(es) constituted token-specific learning and/or generalization. A hybrid learning paradigm comprising pre/post and old/new test comparisons was used. For both participant groups, classification accuracy for old (ie trained) drawings markedly increased over study trials (mean improvement = 76%, and 88%, respectively). Additionally, RT decreased by a mean of 30% for the sighted, and 31% for the adventitiously blind. Learning was mostly token-specific, but some generalization was also observed for both groups. The sighted classified novel drawings of all six FEEs faster with training (mean RT decrease = 20%). Accuracy also improved significantly (mean improvement = 20%), but this improvement was restricted to two FEEs (anger and sadness). Two of three adventitiously blind participants classified new drawings more accurately (mean improvement = 30%); however, RTs for this group did not reflect generalization. Based on a limited number of blind subjects, our results tentatively suggest that adventitiously blind individuals learn to haptically classify FEEs as well as, or even better than, sighted persons.