Issue

Vol. 14 (2022)

An All-In-One Multifunctional Touch Sensor with Carbon-Based Gradient Resistance Elements

https://doi.org/10.1007/s40820-022-00875-9
Chao Wei
Department of Electronic Science, Xiamen University, Xiamen 361005, People’s Republic of China
Wansheng Lin
Department of Electronic Science, Xiamen University, Xiamen 361005, People’s Republic of China
Shaofeng Liang
Department of Electronic Science, Xiamen University, Xiamen 361005, People’s Republic of China
Mengjiao Chen
Department of Electronic Science, Xiamen University, Xiamen 361005, People’s Republic of China
Yuanjin Zheng
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
Xinqin Liao
Department of Electronic Science, Xiamen University, Xiamen 361005, People’s Republic of China
Zhong Chen
Department of Electronic Science, Xiamen University, Xiamen 361005, People’s Republic of China

Corresponding Author: Zhong Chen

chenz@xmu.edu.cn

Nano-Micro Letters, Vol. 14 (2022), Article Number: 131

Abstract

Human–machine interactions using deep-learning methods are important in the research of virtual reality, augmented reality, and metaverse. Such research remains challenging as current interactive sensing interfaces for single-point or multipoint touch input are trapped by massive crossover electrodes, signal crosstalk, propagation delay, and demanding configuration requirements. Here, an all-in-one multipoint touch sensor (AIOM touch sensor) with only two electrodes is reported. The AIOM touch sensor is efficiently constructed by gradient resistance elements, which can highly adapt to diverse application-dependent configurations. Combined with deep learning method, the AIOM touch sensor can be utilized to recognize, learn, and memorize human–machine interactions. A biometric verification system is built based on the AIOM touch sensor, which achieves a high identification accuracy of over 98% and offers a promising hybrid cyber security against password leaking. Diversiform human–machine interactions, including freely playing piano music and programmatically controlling a drone, demonstrate the high stability, rapid response time, and excellent spatiotemporally dynamic resolution of the AIOM touch sensor, which will promote significant development of interactive sensing interfaces between fingertips and virtual objects.


Highlights:


1 Carbon-based gradient resistance element structure is proposed for the construction of multifunctional touch sensor, which will promote wide detection and recognition range of multiple mechanical stimulations.
2 Multifunctional touch sensor with gradient resistance element and two electrodes is demonstrated to eliminate signals crosstalk and prevent interference during position sensing for human–machine interactions.
3 Biological sensing interface based on a deep-learning-assisted all-in-one multipoint touch sensor enables users to efficiently interact with virtual world.

Keywords

Multifunctional touch sensor Carbon functional material Paper-based device Gradient resistance element Human–machine interaction
Wei, Chao, Wansheng Lin, Shaofeng Liang, Mengjiao Chen, Yuanjin Zheng, Xinqin Liao, and Zhong Chen. 2022. “An All-In-One Multifunctional Touch Sensor With Carbon-Based Gradient Resistance Elements”. Nano-Micro Letters 14 (June):131. https://doi.org/10.1007/s40820-022-00875-9.
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