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Classification Method of Rubbing Haptic Information Using Convolutional Neural Network

  • Shotaro AgatsumaEmail author
  • Shinji Nakagawa
  • Tomoyoshi Ono
  • Satoshi Saga
  • Simona Vasilache
  • Shin Takahashi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10904)

Abstract

In previous research, we proposed a method to collect accelerations in daily haptic behaviors using a ZigBee-based microcomputer. However, the method for classifying the collected data was not sufficiently implemented. We therefore propose applying collected data to classify rubbing haptic information. In this paper, we implemented a classification approach for haptic information collected by our method. We used a convolutional neural network (CNN) to classify the information. We performed a classification experiment in which the CNN classified 18 types of information, 93.2% on average. We also performed an experiment to classify rubbed objects in real-time. The CNN was able to classify five types of objects, about 67.7% on average.

Keywords

Zigbee-based microcomputer Haptic information Convolutional neural network 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Shotaro Agatsuma
    • 1
    Email author
  • Shinji Nakagawa
    • 1
  • Tomoyoshi Ono
    • 1
  • Satoshi Saga
    • 2
  • Simona Vasilache
    • 1
  • Shin Takahashi
    • 1
  1. 1.University of TsukubaTsukuba cityJapan
  2. 2.University of KumamotoKumamoto cityJapan

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