Vibrotactile letter reading using a low-resolution tactor array

  • Authors:

  • Yasuyuki Yanagida;Mitsuhiro Kakita;Robert W. Lindeman;Yuichiro Kume;Nobuji Tetsutani

  • Affiliations:

  • Media Information Science Laboratories, ATR, Kyoto, Japan;Media Information Science Laboratories, ATR, Kyoto, Japan and School of Knowledge Science, Japan Advanced Institute of Science & Technology, Ishikawa, Japan;Department of Computer Science, George Washington University, Washington DC and Media Information Science Laboratories, ATR, Kyoto, Japan;Faculty of Engineering, Tokyo Polytechnic University, Kanagawa, Japan and Media Information Science Laboratories, ATR, Kyoto, Japan;Media Information Science Laboratories, ATR, Kyoto, Japan

  • Venue:
  • HAPTICS'04 Proceedings of the 12th international conference on Haptic interfaces for virtual environment and teleoperator systems
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

Abstract

Vibrotactile displays have been studied for several decades in the context of sensory substitution. Recently, a number of vibrotactile displays have been developed to extend sensory modalities in virtual reality. Some of these target the whole body as the stimulation region, but existing systems are only designed for discrete stimulation points at specific parts of the body. However, since human tactile sensation has more resolution, a higher density might be required in tactor alignment in order to realize general-purpose vibrotactile displays. One problem with this approach is that it might result in an impractically high number of required tactors. Our current focus is to explore ways of simplifying the system while maintaining an acceptable level of expressive ability. As a first step, we chose a well-studied task: tactile letter reading. We examined the possibility of distinguishing alphanumeric letters by using only a 3-by- 3 array of vibrating motors on the back of a chair. The tactors are driven sequentially in the same sequence as if someone were tracing the letter on the chair's back. The results showed 87% successful letter recognition in some cases, which was close to the results in previous research with much larger arrays.