Triboelectric bending sensor based smart glove towards intuitive multi-dimensional human-machine interfaces

Abstract

Recent advances in human-machine interface (HMI) lead to a renewed interest in creating intuitive and immersive interaction. Here, we designed a simple-structured and high-resolution bending angle triboelectric sensor named bending-angle triboelectric nanogenerator (BA-TENG) to construct a glove-based multi-dimen- sional HMI. With the assistance of a customized print circuit board (PCB), the glove-based HMI exhibits high sensitivity and low crosstalk in real-time multi-channel finger motion sensing. The signal-to-noise ratio (SNR) is improved by 19.36 dB. By systematically extracting and analyzing the multi-dimensional signal features of the BA-TENG, intuitive multi-dimensional HMIs were realized for smart-home, advanced robotic control, and a virtual keyboard with user recognition functionality. The classification accuracy of the virtual keyboard for seven users reached 93.1% by leveraging the advanced machine learning technique. The proposed BA-TENG-based smart glove reveals its potential as a solution for minimalist-design and intuitive multi-dimensional HMI, promising in diversified areas, including the Internet of things (IoT), assistive technology, and intelligent recognition systems.

Zihan Wang

Ph.D. Candidate

My research interests include soft robot and flexible sensor. Welcome to contact me.