WiFi-Powered Sensor Integrated into a Smart Glove with a Fully Fabric Antenna for the Human–Machine Interface

The integration of flexible sensors into human-machine interfaces (HMIs) is in increasing demand for intuitive and effective manipulation. Traditional glove-based HMIs, constrained by nonconformal rigid structures or the need for bulky batteries, face limitations in continuous operation. Addressing this, we introduce yarn-based bend sensors in our smart glove, which are wirelessly powered and harvest energy from a fully textile 5.8 GHz WiFi-band antenna receiver. These sensors exhibit a gauge factor (GF) of 5.60 for strains ranging from 0 to 10%. They show a consistent performance regardless of the straining frequency when being stretched and released at frequencies between 0.1 and 0.7 Hz. This reliability ensures that the sensor output is solely dependent on the yarn's elongation. Accurately detecting finger-bending movements from 0° to 90° in a virtual environment, the sensors enable enhanced degrees of freedom for human finger interaction. When integrated with advanced machine-learning techniques, the system achieves a classification accuracy of 98.75% for object recognition, demonstrating its potential for precise and accurate HMI. Unlike conventional near-field energy transfer methods that rely on magnetic flux and are limited by power loss over distance, our fully textile design effectively harvests microwave energy, showing no voltage deterioration up to 1 m away. This minimalist microwave-powered smart glove represents a significant advancement, offering a viable and practical solution for developing intuitive and reliable HMIs.

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Institutions

Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2024-11-05
DOI
https://doi.org/10.1021/acsami.4c12371
Citations
8
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
1.48

Funders

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article

WiFi-Powered Sensor Integrated into a Smart Glove with a Fully Fabric Antenna for the Human–Machine Interface

Jen-Hahn Low, Cao Guan, Pei Song Chee, Eng-Hock Lim et al.
8 citations
ACS Applied Materials & Interfaces
Advanced Sensor and Energy Harvesting Materials
1.48
article

WiFi-Powered Sensor Integrated into a Smart Glove with a Fully Fabric Antenna for the Human–Machine Interface

Jen-Hahn Low, Cao Guan, Pei Song Chee, Eng-Hock Lim, Kyung‐Sub Lee, Chun Hui Tan, Kwong-Long Wong
article en
8 citations

Abstract

The integration of flexible sensors into human-machine interfaces (HMIs) is in increasing demand for intuitive and effective manipulation. Traditional glove-based HMIs, constrained by nonconformal rigid structures or the need for bulky batteries, face limitations in continuous operation. Addressing this, we introduce yarn-based bend sensors in our smart glove, which are wirelessly powered and harvest energy from a fully textile 5.8 GHz WiFi-band antenna receiver. These sensors exhibit a gauge factor (GF) of 5.60 for strains ranging from 0 to 10%. They show a consistent performance regardless of the straining frequency when being stretched and released at frequencies between 0.1 and 0.7 Hz. This reliability ensures that the sensor output is solely dependent on the yarn's elongation. Accurately detecting finger-bending movements from 0° to 90° in a virtual environment, the sensors enable enhanced degrees of freedom for human finger interaction. When integrated with advanced machine-learning techniques, the system achieves a classification accuracy of 98.75% for object recognition, demonstrating its potential for precise and accurate HMI. Unlike conventional near-field energy transfer methods that rely on magnetic flux and are limited by power loss over distance, our fully textile design effectively harvests microwave energy, showing no voltage deterioration up to 1 m away. This minimalist microwave-powered smart glove represents a significant advancement, offering a viable and practical solution for developing intuitive and reliable HMIs.

ACS Applied Materials & InterfacesVol. 16(45)
Northwestern Polytechnical University (CN), Universiti Tunku Abdul Rahman (MY)
Collaborative Research in Engineering, Science and Technology Centre
Affordable and clean energy
Openalex Percentile: Top 19%
Advanced Sensor and Energy Harvesting Materials
1.48
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