Journal
ADVANCED MATERIALS
Volume 30, Issue 30, Pages -Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/adma.201801291
Keywords
artificial intelligence; artificial neurons; electronic skin; neuromorphic engineering; perceptual learning
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Funding
- National Research Foundation (NRF), Prime Minister's office, Singapore, under its NRF Investigatorship [NRF2016NRF-NRF1001-21]
- Singapore Ministry of Education [MOE2014-T2-2-140, MOE2017-T2-2-107]
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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 learningthe 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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