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Bio‐Inspired Artificial Perceptual Devices for Neuromorphic Computing and Gesture Recognition.

Authors :
Chen, Fandi
Zhang, Shuo
Hu, Long
Fan, Jiajun
Lin, Chun‐Ho
Guan, Peiyuan
Zhou, Yingze
Wan, Tao
Peng, Shuhua
Wang, Chun‐Hui
Wu, Liao
Furlong, Teri McLean
Valanoor, Nagarajan
Chu, Dewei
Source :
Advanced Functional Materials; 6/12/2023, Vol. 33 Issue 24, p1-10, 10p
Publication Year :
2023

Abstract

Artificial perception technologies capable of sensing and feeling mechanical stimuli like human skins are critical enablers for electronic skins (E‐Skins) needed to achieve artificial intelligence. However, most of the reported electronic skin systems lack the capability to process and interpret the sensor data. Herein, a new design of artificial perceptual system integrating ZnO‐based synaptic devices with Pt/carbon nanofibers‐based strain sensors for stimuli detection and information processing is presented. Benefiting from the controllable ion migration after indium doping, the device can emulate various essential functions, such as short‐term/long‐term plasticity, paired‐pulse facilitation, excitatory post‐synaptic current, and synaptic plasticity depending on the number, frequency, amplitude, and width of the applied pulses. The Pt/carbon nanofibers‐based strain sensors can detect subtle human motion and convert mechanical stimuli into electrical signals, which are further processed by the ZnO devices. By attaching the integrated devices to finger joints, it is demonstrated that they can recognize handwriting and gestures with a high accuracy. This work offers new insights in designing artificial synapses and sensors to process and recognize information for neuromorphic computing and artificial intelligence applications. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1616301X
Volume :
33
Issue :
24
Database :
Complementary Index
Journal :
Advanced Functional Materials
Publication Type :
Academic Journal
Accession number :
164256060
Full Text :
https://doi.org/10.1002/adfm.202300266