An artificial sensory neuron with tactile perceptual learning

Autor: Qing Wan, Changjin Wan, Liang Pan, Geng Chen, Yangming Fu, Xiaodong Chen, Li Qiang Zhu, Naoji Matsuhisa, Ming Wang, Hui Yang, Shaowu Pan
Přispěvatelé: School of Materials Science & Engineering, Innovative Center for Flexible Devices
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Popis: 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. NRF (Natl Research Foundation, S’pore) MOE (Min. of Education, S’pore) Accepted version
Databáze: OpenAIRE