A calibratable sensory neuron based on epitaxial VO2 for spike-based neuromorphic multisensory system

Rui Yuan, Qingxi Duan, Pek Jun Tiw, Ge Li, Zhuojian Xiao, Zhaokun Jing, Ke Yang, Chang Liu, Chen Ge, Ru Huang () and Yuchao Yang ()
Additional contact information
Rui Yuan: Peking University
Qingxi Duan: Peking University
Pek Jun Tiw: Peking University
Ge Li: Chinese Academy of Sciences
Zhuojian Xiao: Peking University
Zhaokun Jing: Peking University
Ke Yang: Peking University
Chang Liu: Peking University
Chen Ge: Chinese Academy of Sciences
Ru Huang: Peking University
Yuchao Yang: Peking University

Nature Communications, 2022, vol. 13, issue 1, 1-12

Abstract: Abstract Neuromorphic perception systems inspired by biology have tremendous potential in efficiently processing multi-sensory signals from the physical world, but a highly efficient hardware element capable of sensing and encoding multiple physical signals is still lacking. Here, we report a spike-based neuromorphic perception system consisting of calibratable artificial sensory neurons based on epitaxial VO2, where the high crystalline quality of VO2 leads to significantly improved cycle-to-cycle uniformity. A calibration resistor is introduced to optimize device-to-device consistency, and to adapt the VO2 neuron to different sensors with varied resistance level, a scaling resistor is further incorporated, demonstrating cross-sensory neuromorphic perception component that can encode illuminance, temperature, pressure and curvature signals into spikes. These components are utilized to monitor the curvatures of fingers, thereby achieving hand gesture classification. This study addresses the fundamental cycle-to-cycle and device-to-device variation issues of sensory neurons, therefore promoting the construction of neuromorphic perception systems for e-skin and neurorobotics.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://www.nature.com/articles/s41467-022-31747-w Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-31747-w

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-022-31747-w

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().