Using Spatiotemporal Modulation to Draw Tactile Patterns in Mid-Air

  • William FrierEmail author
  • Damien Ablart
  • Jamie Chilles
  • Benjamin Long
  • Marcello Giordano
  • Marianna Obrist
  • Sriram Subramanian
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10893)


One way to create mid-air haptics is to use an ultrasonic phased-array, whose elements may be controlled to focus acoustic pressure to points in space (referred to as focal points). At these focal points the pressure can then deflect off the skin and induce a tactile sensation. Furthermore, by rapidly and repeatedly updating the position of a focal point over a given trajectory, ultrasound phased-array can draw two dimensional curves (referred to as patterns) on a users’ palms. While producing these patterns, there are three major parameters at play: the rate at which the pattern is repeated, the pattern length, and the focal point speed. Due to the interdependence between these parameters, only the repetition rate (frequency) or the speed can be set for a tactile pattern of a given length. In the current study, we investigate which approach (frequency or speed) is most effective at maximising the tactile sensation. We first carried out a vibrometry study to show that optimising the speed can maximise the skin deflection caused by a focal point following circular patterns. A further user study was undertaken to show that optimising the speed consequently maximises the perceived intensity of the tactile pattern. In both studies, the optimal speed result is shown to be equivalent to the speed at which surface waves propagate from the skin deflection effected by the focal point. Overall, our investigations highlight the importance of the speed of stimulation movement in the design of tactile patterns.


Tactile Pattern Spatiotemporal Modulation Ultrasound Phased Array Surface Wave Propagation Circle Circumference 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to thank the Directors of Ultrahaptics for their support. This research has received funding from the European Union’s Horizon 2020 programme No. 638605 and No. 737087.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • William Frier
    • 1
    Email author
  • Damien Ablart
    • 1
  • Jamie Chilles
    • 2
  • Benjamin Long
    • 2
  • Marcello Giordano
    • 2
  • Marianna Obrist
    • 1
  • Sriram Subramanian
    • 1
  1. 1.University of SussexBrightonUK
  2. 2.Ultrahaptics Ltd.BristolUK

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