An Artificial Sensory Neuron with Tactile Perceptual Learning

Changjin Wan, Geng Chen, Yangming Fu, Ming Wang, Naoji Matsuhisa, Shaowu Pan, Liang Pan, Hui Yang, Qing Wan, Liqiang Zhu, Xiaodong Chen

Research output: Contribution to journalArticlepeer-review

134 Citations (Scopus)

Abstract

Sensory neurons within skin form an interface between the external physical reality and the inner tactile perception. This interface enables sensory information to be organized identified, and interpreted through perceptual learning—the process whereby the sensing abilities improve through experience. Here, an artificial sensory neuron that can integrate and differentiate the spatiotemporal features of touched patterns for recognition is shown. The system comprises sensing, transmitting, and processing components that are parallel to those found in a sensory neuron. A resistive pressure sensor converts pressure stimuli into electric signals, which are transmitted to a synaptic transistor through interfacial ionic/electronic coupling via a soft ionic conductor. Furthermore, the recognition error rate can be dramatically decreased from 44% to 0.4% by integrating with the machine learning method. This work represents a step toward the design and use of neuromorphic electronic skin with artificial intelligence for robotics and prosthetics.

Original languageEnglish
Article number1801291
JournalAdvanced Materials
Volume30
Issue number30
DOIs
Publication statusPublished - 2018 Jul 26
Externally publishedYes

Keywords

  • artificial intelligence
  • artificial neurons
  • electronic skin
  • neuromorphic engineering
  • perceptual learning

ASJC Scopus subject areas

  • Materials Science(all)
  • Mechanics of Materials
  • Mechanical Engineering

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