Enhanced Reach: Assisting Social Interaction Based on Geometric Relationships

  • Asaki Miura
  • Dushyantha Jayatilake
  • Kenji Suzuki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7822)


Social interaction among children plays a significant role in their social development. Some children, however, find it difficult to initiate interaction and there are only few tools that can create opportunities for children to interact with others.

This study presents a small wireless device that can measure and visualize geometric relationships in a gymnasium or playground. The estimation of geometric relationships is proposed based on signal strength of wireless communication, bodily orientation and statistical geometric consistency. A light-emitting visualization method is used in real-time according to geometric relationships among devices. Several wearable interfaces were developed to facilitate communication and social interaction of children by using the developed wireless device. Several experiments were done with typically developing children and children with pervasive developmental disorders (PDD) to evaluate the proposed technology.


Group Dynamic Inertia Measurement Unit Receive Signal Strength Indicator Pervasive Developmental Disorder Pervasive Developmental Disorder 
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.


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  1. 1.
    Howe, C., Mercer, N.: Children’s social development, peer interaction and classroom learning. Primary Review Research Survey, 2/1b (2007)Google Scholar
  2. 2.
    Farr, W., Yuill, N., Harris, E., Hinske, S.: In my own words: configuration of tangibles, object interaction and children with autism. In: Proc. of the 9th Int. Conf. on Interaction Design and Children, pp. 30–38 (2010)Google Scholar
  3. 3.
    Lund, H.H., Jessen, C.: Playware technology for physically activating play. Artificial Life and Robotics 9(4), 165–174 (2005)CrossRefGoogle Scholar
  4. 4.
    Shaw, M.E.: Group dynamics: The psychology of small group behavior. McGraw Hill (1971)Google Scholar
  5. 5.
    Ohyama, S., Yamada, S., Takayama, J.: Sensor node localization based on inequalities of radio field intensity - comparison of simulation and experiments. In: Proc. of SICE-ICASE International Joint Conference, pp. 1947–1952 (2006)Google Scholar
  6. 6.
    Sammon, J.W.: A nonlinear mapping for data structure analysis. IEEE Transactions on Computers C-18(5), 401–409 (1969)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Asaki Miura
    • 1
  • Dushyantha Jayatilake
    • 1
  • Kenji Suzuki
    • 1
  1. 1.Artificial Intelligence LaboratoryUniversity of TsukubaJapan

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