In this work, we focus on finding and characterizing stereotypical behavioral modes during haptic search in an unstructured 3D display. To this end, we introduce the notion of search procedures and present a machine learning approach for their identification. Search procedures are derived from the haptic exploratory procedures (EPs) through their parameterization and, in some cases, their mixture. In order to identify representative search procedures, we have evaluated data of eight individuals who performed a one-handed haptic search task in nine different scenarios, blindfolded. In all cases, they were asked to localize a specific target object within a tactile scene. Both the target object and the scene were formed from wooden bricks of various tactile shapes arranged in a configurable haptic display to exhibit a specific 3D tactile pattern. By performing t-SNE-based dimensionality reduction and subsequent k-means clustering, we could identify three representative types of search procedures during manual haptic search: 1) one finger performs one EP 2) several fingers and the hand perform a differently parameterized EPs in a parallel manner 3) a mixture of EPs is performed by the hand and fingers in a parallel manner. We exemplify the notion of search procedures and discuss the corresponding mixtures based on the results of the clustering.
['Alexandra Moringen', 'Robert Haschke', 'Helge Ritter']
Search procedures during haptic search in an unstructured 3D display