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Title: An artificial sensory neuron with tactile perceptual learning
Authors: Wan, Changjin
Chen, Geng
Fu, Yangming
Wang, Ming
Matsuhisa, Naoji
Pan, Shaowu
Pan, Liang
Yang, Hui
Wan, Qing
Zhu, Liqiang
Chen, Xiaodong
Keywords: Engineering::Materials
Issue Date: 2018
Source: Wan, C., Chen, G., Fu, Y., Wang, M., Matsuhisa, N., Pan, S., . . ., Chen, X. (2018). An artificial sensory neuron with tactile perceptual learning. Advanced materials, 30(30), 1801291-. doi:10.1002/adma.201801291
Journal: Advanced materials 
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.
ISSN: 0935-9648
DOI: 10.1002/adma.201801291
Schools: School of Materials Science & Engineering 
Organisations: Innovative Center for Flexible Devices 
Rights: © 2018 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim. All rights reserved. This paper was published in Advanced materials and is made available with permission of WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MSE Journal Articles

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