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Self-Powered Gesture Recognition Wristband Enabled by Machine Learning for Full Keyboard and Multicommand Input

Authors :
Puchuan Tan
Xi Han
Yang Zou
Xuecheng Qu
Jiangtao Xue
Tong Li
Yiqian Wang
Ruizeng Luo
Xi Cui
Yuan Xi
Le Wu
Bo Xue
Dan Luo
Yubo Fan
Xun Chen
Zhou Li
Zhong Lin Wang
Source :
Advanced materials (Deerfield Beach, Fla.). 34(21)
Publication Year :
2022

Abstract

Virtual reality is a brand-new technology that can be applied extensively. To realize virtual reality, certain types of human-computer interaction equipment are necessary. Existing virtual reality technologies often rely on cameras, data gloves, game pads, and other equipment. These equipment are either bulky, inconvenient to carry and use, or expensive to popularize. Therefore, the development of a convenient and low-cost high-precision human-computer interaction device can contribute positively to the development of virtual reality technology. In this study, a gesture recognition wristband that can realize a full keyboard and multicommand input is developed. The wristband is convenient to wear, low in cost, and does not affect other daily operations of the hand. This wristband is based on physiological anatomy as well as aided by active sensor and machine learning technology; it can achieve a maximum accuracy of 92.6% in recognizing 26 letters. This wristband offers broad application prospects in the fields of gesture command recognition, assistive devices for the disabled, and wearable electronics.

Details

ISSN :
15214095
Volume :
34
Issue :
21
Database :
OpenAIRE
Journal :
Advanced materials (Deerfield Beach, Fla.)
Accession number :
edsair.doi.dedup.....9839041af481f79b54160bbb4491e80c