Abstract
Several studies have investigated the relevance of haptics to physically convey various types of emotion. However, they use basic analysis approaches to identify the relevant features for an effective communication of emotion. This article presents an advanced analysis approach, based on the clustering technique, that enables the extraction of the general features of affective haptic expressions as well as the identification of specific features in order to discriminate between close emotions that are difficult to differentiate. This approach was tested in the context of affective communication through a virtual handshake. It uses a haptic device, which enables the expression of 3D movements. The results of this research were compared to those of the standard Analysis of Variance method in order to highlight the advantages and limitations of each approach.
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