Liu, Y., Liang, X., Li, H., Deng, H., Zhang, X., Wen, D., Yuan, M., Heidari, H. , Ghannam, R. and Zhang, X. (2022) Ultralight smart patch with reduced sensing array based on reduced graphene oxide for hand gesture recognition. Advanced Intelligent Systems, 4(11), 2200193. (doi: 10.1002/aisy.202200193)
Text
281134.pdf - Published Version Available under License Creative Commons Attribution. 4MB |
Abstract
Flexible sensors for hand gesture recognition and human–machine interface (HMI) applications have witnessed tremendous advancements during the last decades. Current state-of-the-art sensors placed on fingers or embedded into gloves are incapable of fully capturing all hand gestures and are often uncomfortable for the wearer. Herein, a flake-sphere hybrid structure of reduced graphene oxide (rGO) doped with polystyrene (PS) spheres is fabricated to construct the highly sensitive, fast response, and flexible piezoresistive sensor array, which is ultralight in the weight of only 2.8 g and possesses the remarkable curved-surface conformability. The flexible wrist-worn device with a five-sensing array is used to measure pressure distribution around the wrist for accurate and comfortable hand gesture recognition. The intelligent wristband is able to classify 12 hand gestures with 96.33% accuracy for five participants using a machine learning algorithm. To showcase our wristband, a real-time system is developed to control a robotic hand via the classification results, which further demonstrates the potential of this work for HMI applications.
Item Type: | Articles |
---|---|
Additional Information: | This work was financially supported by the National Natural Science Foundation of China (grant nos. 62074029, 61804023, and 61971108), the Key R&D Program of Sichuan Province (grant nos. 2022JDTD0020 and 2020ZHCG0038), the Sichuan Science and Technology Program (grant nos. 2019YJ0198 and 2020YJ0015), and the Fundamental Research Funds for the Central Universities (grant no. ZYGX2019Z002). |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Yuan, Miss Mengyao and Liang, Mr Xiangpeng and Ghannam, Professor Rami and Heidari, Professor Hadi and Liu, Miss Yuchi |
Authors: | Liu, Y., Liang, X., Li, H., Deng, H., Zhang, X., Wen, D., Yuan, M., Heidari, H., Ghannam, R., and Zhang, X. |
College/School: | College of Science and Engineering > School of Engineering College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering |
Journal Name: | Advanced Intelligent Systems |
Publisher: | Wiley |
ISSN: | 2640-4567 |
ISSN (Online): | 2640-4567 |
Published Online: | 06 October 2022 |
Copyright Holders: | Copyright © 2022 The Authors |
First Published: | First published in Advanced Intelligent Systems 4(11): 2200193 |
Publisher Policy: | Reproduced under a Creative Commons License |
University Staff: Request a correction | Enlighten Editors: Update this record