TY - CONF T1 - Tactile Slip and Hand Displacement: Bending Hand Motion with Tactile Illusions T2 - IEEE World Haptic Conference Y1 - 2017 A1 - M. Bianchi A1 - A. Moscatelli A1 - S. Ciotti A1 - G. C. Bettelani A1 - F. Fioretti A1 - F. Lacquaniti A1 - A. Bicchi KW - Haptics AB -

Touch provides an important cue to perceive the physical properties of the external objects. Recent studies showed that tactile sensation also contributes to our sense of hand position and displacement in perceptual tasks. In this study, we tested the hypothesis that, sliding our hand over a stationary surface, tactile motion may provide a feedback for guiding hand trajectory. We asked participants to touch a plate having parallel ridges at different orientations and to perform a self-paced, straight movement of the hand. In our daily-life experience, tactile slip motion is equal and opposite to hand motion. Here, we used a well-established perceptual illusion to dissociate, in a controlled manner, the two motion estimates. According to previous studies, this stimulus produces a bias in the perceived direction of tactile motion, predicted by tactile flow model. We showed a systematic deviation in the movement of the hand towards a direction opposite to the one predicted by tactile flow, supporting the hypothesis that touch contributes to motor control of the hand. We suggested a model where the perceived hand motion is equal to a weighted sum of the estimate from classical proprioceptive cues (e.g., from musculoskeletal system) and the estimate from tactile slip.

JF - IEEE World Haptic Conference PB - IEEE CY - Fürstenfeldbruck (Munich), Germany, June 6-9, 2017 N1 -

 This work is supported in part by the European Research Council under the Advanced Grant SoftHands “A Theory of Soft Synergies for a New Generation of Artificial Hands” no. ERC-291166, by the EU H2020 project “SOFTPRO: Synergy-based Open-source Foundations and Technologies for Prosthetics and RehabilitatiOn” (no. 688857) and by the EU FP7 project (no. 601165), “WEARable HAPtics for Humans and Robots (WEARHAP)”. We thank Priscilla Balestrucci and Colleen P. Ryan for helpful comments and suggestions.

ER -