Classification Method of Rubbing Haptic Information Using Convolutional Neural Network

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10904)


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.


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

  1. 1.University of TsukubaTsukuba cityJapan
  2. 2.University of KumamotoKumamoto cityJapan

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