An Artificial Sensory Neuron with Tactile Perceptual Learning |
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| Authors: | Changjin Wan Geng Chen Yangming Fu Ming Wang Naoji Matsuhisa Shaowu Pan Liang Pan Hui Yang Qing Wan Liqiang Zhu Xiaodong Chen |
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| Affiliation: | 1. Innovative Center for Flexible Devices (iFLEX), School of Materials Science and Engineering Nanyang Technological University, Singapore;2. Key Laboratory of Graphene Technologies and Applications of Zhejiang Province, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang, P. R. China;3. School of Electronic Science and Engineering, Nanjing University, Nanjing, Jiangsu, P. R. China |
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| 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. |
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| Keywords: | artificial intelligence artificial neurons electronic skin neuromorphic engineering perceptual learning |
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