Haptic-feedback smart glove as a creative human-machine interface (HMI) for virtual/augmented reality applications

Minglu Zhu; Zhongda Sun; Zixuan Zhang; Qiongfeng Shi; Tianyiyi He; Huicong Liu; Tao Chen; Chengkuo Lee

doi:10.1126/sciadv.aaz8693

Haptic-feedback smart glove as a creative human-machine interface (HMI) for virtual/augmented reality applications

Sci Adv. 2020 May 8;6(19):eaaz8693. doi: 10.1126/sciadv.aaz8693. eCollection 2020 May.

Authors

Minglu Zhu^{1

2

3

4}, Zhongda Sun^{1

2

3}, Zixuan Zhang^{1

2

3}, Qiongfeng Shi^{1

2

3}, Tianyiyi He^{1

2

3

4}, Huicong Liu⁵, Tao Chen⁵, Chengkuo Lee^{1

2

3

4

6}

Affiliations

¹ Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117576, Singapore.
² Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, 5 Engineering Drive 1, Singapore 117608, Singapore.
³ Hybrid Integrated Flexible Electronic Systems (HIFES), 5 Engineering Drive 1, Singapore 117608, Singapore.
⁴ National University of Singapore Suzhou Research Institute (NUSRI), Suzhou Industrial Park, Suzhou 215123, China.
⁵ Jiangsu Provincial Key Laboratory of Advanced Robotics, School of Mechanical and Electric Engineering, Soochow University, Suzhou 215123, China.
⁶ NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore 119077, Singapore.

Abstract

Human-machine interfaces (HMIs) experience increasing requirements for intuitive and effective manipulation. Current commercialized solutions of glove-based HMI are limited by either detectable motions or the huge cost on fabrication, energy, and computing power. We propose the haptic-feedback smart glove with triboelectric-based finger bending sensors, palm sliding sensor, and piezoelectric mechanical stimulators. The detection of multidirectional bending and sliding events is demonstrated in virtual space using the self-generated triboelectric signals for various degrees of freedom on human hand. We also perform haptic mechanical stimulation via piezoelectric chips to realize the augmented HMI. The smart glove achieves object recognition using machine learning technique, with an accuracy of 96%. Through the integrated demonstration of multidimensional manipulation, haptic feedback, and AI-based object recognition, our glove reveals its potential as a promising solution for low-cost and advanced human-machine interaction, which can benefit diversified areas, including entertainment, home healthcare, sports training, and medical industry.

Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).