International Journal of Social Robotics

, Volume 6, Issue 4, pp 489–505 | Cite as

Interpretation of Social Touch on an Artificial Arm Covered with an EIT-based Sensitive Skin

  • David Silvera-TawilEmail author
  • David Rye
  • Mari Velonaki


During social interaction humans extract important information from tactile stimuli that improves their understanding of the interaction. The development of a similar capacity in a robot will contribute to the future success of intuitive human–robot interactions. This paper presents experiments on the classification of social touch on a full-sized mannequin arm covered with touch-sensitive artificial skin. The flexible and stretchable sensitive skin was implemented using electrical impedance tomography. A classifier based on the LogitBoost algorithm was used to classify six emotions and six social messages transmitted by humans when touching the artificial arm. Experimental results show that classification of social touch can be achieved with accuracies comparable to those achieved by humans.


Social touch Human–robot interaction (HRI) Social robotics Supervised machine learning LogitBoost  Artificial sensitive skin Electrical impedance tomography 


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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Creative Robotics Lab, National Institute for Experimental ArtsUniversity of New South WalesKensingtonAustralia
  2. 2.Centre for Social Robotics, Australian Centre for Field RoboticsThe University of SydneyDarlingtonAustralia

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